Plasma Metabolites Forecast Occurrence and Prognosis for Patients With Diffuse Large B-Cell Lymphoma

Serum NMR metabolomics in distinct subtypes of hematologic malignancies

Hematologic malignancies encompass a diverse array of subtypes, contributing to substantial heterogeneity that poses challenges in predicting clinical outcomes. Leveraging the capabilities of nuclear magnetic resonance holds substantial promise in the detection of serum biomarkers and individual metabolic alterations in patients. This study involved the analysis of the sera from patients with acute myeloid leukemia, chronic lymphocytic leukemia, and non-Hodgkin lymphoma to investigate the affected metabolites and their associated pathways. The quantitative one-dimensional (1D) 1H nuclear magnetic resonance method was employed to identify alterations. Metabolite annotations were validated using two-dimensional (2D) analyses. Discriminating chemometric models and receiver operating characteristic curves were created using the MetaboAnalyst platform. The findings revealed significant alterations in the serum levels of amino acid catabolism products, citrate cycle intermediates, and phospholipids. The acute myeloid leukemia group showed differences in glucogenic amino acids related to the glycolysis pathway, whereas the chronic lymphocytic leukemia and non-Hodgkin lymphoma groups displayed variances in fumarate and acetate levels linked to the citrate cycle pathway. In the leukemia groups, higher levels of products from the protein degradation pathway were observed. The biomarker panels for each malignancy group exhibited outstanding discrimination from controls. Healthy individuals differed distinctly from patients, indicating commonly observed metabolic adaptation patterns among frequent hematologic malignancies. The small cohort study using nuclear magnetic resonance metabolomics in various hematologic malignancy subtypes revealed significant changes in serum amino acid and protein degradation end-product levels, suggesting prolonged leukocyte lifespan and increased energy demand.

Ketone Bodies Are Potential Prognostic Biomarkers in Relapsed/Refractory Diffuse Large B-Cell Lymphoma: Results from the R2-GDP-GOTEL Trial

Background: Patients with relapsed or refractory (R/R) diffuse large B-cell lymphoma (DLBCL) who are ineligible for high-dose chemotherapy have limited treatment options and poor life expectancy. The purpose of this study is to identify a serum metabolomic profile that may be predictive of outcome in patients with R/R-DLBCL. Methods: This study included 69 R/R DLBCL patients from the R2-GDP-GOTEL trial (EudraCT 2014-001620-299). Serum samples were collected at baseline, and the mean length of follow-up was 41 months. Serum metabolites were analyzed by nuclear magnetic resonance (NMR). Metabolites were correlated with treatment response, progression-free survival (PFS), and overall survival (OS). Results: Serum levels of 3-hydroxybutyrate (3OHB) and acetone were significantly (p < 0.001) associated with PFS (3OHB: hazard ratio [HR] 7.7, 95% confidence interval [CI] 2.5-24.1; acetone: HR 9.32, 95% CI 2.75-31.6) and OS (3OHB: HR 9.32, 95% CI 2.75-31.6; acetone: HR 1.92, 95% CI 1.36-2.69). Serum values of 141 µM for 3OHB and 40 µM for acetone were the optimal cutoffs associated with the survival outcomes. Elevated 3OHB levels (>141 μM) were specific to the ABC subtype of DLBCL, while acetone levels were elevated in both types of DLCBL but more pronounced in ABC cases. In a multivariate survival analysis, including the International Prognostic Index (IPI) score and refractoriness status (R/R), 3OHB and acetone remained significant. To aid oncologists employing the R2-GDP regime, we constructed PFS and OS nomograms for R/R-DLBCL risk stratification, incorporating 3OHB levels or acetone levels, IPI score, and refractoriness status. The nomogram with 3OHB and refractoriness status showed a time-dependent AUC of 0.86 for 6-month PFS and 0.84 for 12-month OS. These nomograms provide a comprehensive tool for individualized risk assessment and treatment optimization. Conclusions: The ketone bodies 3OHB and acetone are potential prognostic biomarkers of poor outcome in R/R DLBCL patients treated with the R2-GDP regimen, independently of IPI score and chemorefractoriness status.

Metabolomics for hematologic malignancies: Advances and perspective

With the use of advanced technology, metabolomics allows for a thorough examination of metabolites and other small molecules found in biological specimens, blood, and tissues. In recent years, metabolomics has been recognized that is closely related to the development of malignancies in the hematological system. Alterations in metabolomic pathways and networks are important in the pathogenesis of hematologic malignancies and can also provide a theoretical basis for early diagnosis, efficacy evaluation, accurate staging, and individualized targeted therapy. In this review, we summarize the progress of metabolomics, including glucose metabolism, amino acid metabolism, and lipid metabolism in lymphoma, myeloma, and leukemia through specific mechanisms and pathways. The research of metabolomics gives a new insight and provides therapeutic targets for the treatment of patients with hematologic malignancies.

Single-cell and spatial transcriptomics reveal a high glycolysis B cell and tumor-associated macrophages cluster correlated with poor prognosis and exhausted immune microenvironment in diffuse large B-cell lymphoma

BACKGROUND

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous malignancy characterized by varied responses to treatment and prognoses. Understanding the metabolic characteristics driving DLBCL progression is crucial for developing personalized therapies.

METHODS

This study utilized multiple omics technologies including single-cell transcriptomics (n = 5), bulk transcriptomics (n = 966), spatial transcriptomics (n = 10), immunohistochemistry (n = 34), multiple immunofluorescence (n = 20) and to elucidate the metabolic features of highly malignant DLBCL cells and tumor-associated macrophages (TAMs), along with their associated tumor microenvironment. Metabolic pathway analysis facilitated by scMetabolism, and integrated analysis via hdWGCNA, identified glycolysis genes correlating with malignancy, and the prognostic value of glycolysis genes (STMN1, ENO1, PKM, and CDK1) and TAMs were verified.

RESULTS

High-glycolysis malignant DLBCL tissues exhibited an immunosuppressive microenvironment characterized by abundant IFN_TAMs (CD68+CXCL10+PD-L1+) and diminished CD8+ T cell infiltration. Glycolysis genes were positively correlated with malignancy degree. IFN_TAMs exhibited high glycolysis activity and closely communicating with high-malignancy DLBCL cells identified within datasets. The glycolysis score, evaluated by seven genes, emerged as an independent prognostic factor (HR = 1.796, 95% CI: 1.077-2.995, p = 0.025 and HR = 2.631, 95% CI: 1.207-5.735, p = 0.015) along with IFN_TAMs were positively correlated with poor survival (p < 0.05) in DLBCL. Immunohistochemical validation of glycolysis markers (STMN1, ENO1, PKM, and CDK1) and multiple immunofluorescence validation of IFN_TAMs underscored their prognostic value (p < 0.05) in DLBCL.

CONCLUSIONS

This study underscores the significance of glycolysis in tumor progression and modulation of the immune microenvironment. The identified glycolysis genes and IFN_TAMs represent potential prognostic markers and therapeutic targets in DLBCL.

Metabolomic biomarkers in liquid biopsy: accurate cancer diagnosis and prognosis monitoring

Liquid biopsy, a novel detection method, has recently become an active research area in clinical cancer owing to its unique advantages. Studies on circulating free DNA, circulating tumor cells, and exosomes obtained by liquid biopsy have shown great advances and they have entered clinical practice as new cancer biomarkers. The metabolism of the body is dynamic as cancer originates and progresses. Metabolic abnormalities caused by cancer can be detected in the blood, sputum, urine, and other biological fluids via systemic or local circulation. A considerable number of recent studies have focused on the roles of metabolic molecules in cancer. The purpose of this review is to provide an overview of metabolic markers from various biological fluids in the latest clinical studies, which may contribute to cancer screening and diagnosis, differentiation of cancer typing, grading and staging, and prediction of therapeutic response and prognosis.

The Metabolism and Immune Environment in Diffuse Large B-Cell Lymphoma

Cells utilize different metabolic processes to maintain their growth and differentiation. Tumor cells have made some metabolic changes to protect themselves from malnutrition. These metabolic alterations affect the tumor microenvironment and macroenvironment. Developing drugs targeting these metabolic alterations could be a good direction. In this review, we briefly introduce metabolic changes/regulations of the tumor macroenvironment and microenvironment and summarize potential drugs targeting the metabolism in diffuse large B-cell lymphoma.

Metabolomics: A New Era in the Diagnosis or Prognosis of B-Cell Non-Hodgkin's Lymphoma

A wide range of histological as well as clinical properties are exhibited by B-cell non-Hodgkin's lymphomas. These properties could make the diagnostics process complicated. The diagnosis of lymphomas at an initial stage is essential because early remedial actions taken against destructive subtypes are commonly deliberated as successful and restorative. Therefore, better protective action is needed to improve the condition of those patients who are extensively affected by cancer when diagnosed for the first time. The development of new and efficient methods for early detection of cancer has become crucial nowadays. Biomarkers are urgently needed for diagnosing B-cell non-Hodgkin's lymphoma and assessing the severity of the disease and its prognosis. New possibilities are now open for diagnosing cancer with the help of metabolomics. The study of all the metabolites synthesised in the human body is called "metabolomics." A patient's phenotype is directly linked with metabolomics, which can help in providing some clinically beneficial biomarkers and is applied in the diagnostics of B-cell non-Hodgkin's lymphoma. In cancer research, it can analyse the cancerous metabolome to identify the metabolic biomarkers. This review provides an understanding of B-cell non-Hodgkin's lymphoma metabolism and its applications in medical diagnostics. A description of the workflow based on metabolomics is also provided, along with the benefits and drawbacks of various techniques. The use of predictive metabolic biomarkers for the diagnosis and prognosis of B-cell non-Hodgkin's lymphoma is also explored. Thus, we can say that abnormalities related to metabolic processes can occur in a vast range of B-cell non-Hodgkin's lymphomas. The metabolic biomarkers could only be discovered and identified as innovative therapeutic objects if we explored and researched them. In the near future, the innovations involving metabolomics could prove fruitful for predicting outcomes and bringing out novel remedial approaches.