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

SummaryDiffuse Large B-cell Lymphoma (DLBCL) is the most prevalent subtype of non-Hodgkin’s lymphoma for which current therapeutic strategies remain insufficient. The diffuse nature of DLBCL, lacking distinct tissue structures, represents a challenge to elucidate the cellular organization and interactions within the tumor microenvironment (TME). In this study, we applied spatial transcriptomics to identify spatially-resolved gene expression profiles in 10 DLBCL tissue samples, identifying distinct immune cell infiltration and colocalization patterns. These profiles were classified into six cellular ecosystems (Cell-Eco) that differ in cellular composition, functional patterns, and neighborhood characteristics. The spatially-resolved Cell-Eco signatures provided prognostic scores that stratified patients with different overall survival rates. We also found that C1q+ tumor-associated macrophages are the primary cells interacting with malignant B cells and influencing the spatial architecture of the TME. This study provides novel biological insights into the complexity of the TME in DLBCL and highlights the potential prognostic value of its spatial organization.Graphical abstractKey findingsSpatial transcriptomics classifies DLBCL tissues based on immune cell infiltration and colocalization patterns.DLBCL tumor microenvironment consists of cellular ecosystems (Cell-Eco) that differ in cellular composition, transcriptomic profiles and neighborhood characteristics.Spatially-resolved Cell-Eco signatures stratify patients with different overall survival.C1q+ tumor-associated macrophages primarily interact with malignant B cells and contribute to the spatial organization of the tumor microenvironment.

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Metabolic reprogramming and therapeutic resistance in primary and metastatic breast cancer

Liu,

Zhang,

Wang

et al. 2024

Mol Cancer

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Metabolic alterations, a hallmark of cancer, enable tumor cells to adapt to their environment by modulating glucose, lipid, and amino acid metabolism, which fuels rapid growth and contributes to treatment resistance. In primary breast cancer, metabolic shifts such as the Warburg effect and enhanced lipid synthesis are closely linked to chemotherapy failure. Similarly, metastatic lesions often display distinct metabolic profiles that not only sustain tumor growth but also confer resistance to targeted therapies and immunotherapies. The review emphasizes two major aspects: the mechanisms driving metabolic resistance in both primary and metastatic breast cancer, and how the unique metabolic environments in metastatic sites further complicate treatment. By targeting distinct metabolic vulnerabilities at both the primary and metastatic stages, new strategies could improve the efficacy of existing therapies and provide better outcomes for breast cancer patients. Supplementary Information The online version contains supplementary material available at 10.1186/s12943-024-02165-x.

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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

Cited by 4 publications

References 94 publications

Predicting lymphoma prognosis using machine learning-based genes associated with lactylation

Predicting lymphoma prognosis using machine learning-based genes associated with lactylation

Spatial transcriptomics unveils immune cellular ecosystems associated with patient survival in diffuse large B-cell lymphoma

Metabolic reprogramming and therapeutic resistance in primary and metastatic breast cancer

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