Prognostic implications of high- OXPHOS macrophages in gastric cancer: a single-cell transcriptomics and tumor microenvironment communication study.
[BACKGROUND] Gastric cancer (GC) is characterized by heterogeneous tumor microenvironment (TME) with various cell types contributing to disease progression and patient outcomes.
- p-value P<0.05
APA
Lin Z, Xu Y, et al. (2025). Prognostic implications of high- OXPHOS macrophages in gastric cancer: a single-cell transcriptomics and tumor microenvironment communication study.. Frontiers in oncology, 15, 1533990. https://doi.org/10.3389/fonc.2025.1533990
MLA
Lin Z, et al.. "Prognostic implications of high- OXPHOS macrophages in gastric cancer: a single-cell transcriptomics and tumor microenvironment communication study.." Frontiers in oncology, vol. 15, 2025, pp. 1533990.
PMID
40620715
Abstract
[BACKGROUND] Gastric cancer (GC) is characterized by heterogeneous tumor microenvironment (TME) with various cell types contributing to disease progression and patient outcomes. This study aims to dissect the single-cell transcriptomic landscape of GC, highlighting the role of tumor-associated macrophages (TAMs) and establishing a novel prognostic signature based on high oxidative phosphorylation (OXPHOS) macrophages.
[METHODS] Single-cell sequencing data from paired GC and normal stomach tissues, obtained from the GEO database (GSE184198), were processed to reveal cellular heterogeneity and identify TAM subsets with high OXPHOS activity. Using the TCGA STAD dataset, survival analyses were conducted on 435 GC patients to establish a high-OXPHOS-macrophage-related prognostic signature.
[RESULTS] We identified eight distinct cell types within the GC TME, indicating significant cellular heterogeneity. Macrophages, particularly TAMs, were found in greater numbers in tumor tissue, with the C3 macrophage subset exhibiting the highest OXPHOS score. A 19-gene high-OXPHOS-macrophage-related prognostic signature was constructed, stratifying patients into different risk categories with significant survival differences (P<0.05). NPC2, LY96, and TPP1 were identified as key macrophage-expressed markers, correlating with prognosis. Cell communication analysis revealed increased interaction in tumor tissues, especially involving NPC2, LY96, and TPP1 positive macrophages, which facilitated tumorigenesis and immune evasion.
[CONCLUSION] The high-OXPHOS-macrophage-related prognostic signature derived from scRNA-seq data provides valuable insights into GC patient stratification. NPC2, LY96, and TPP1, highly expressed in TAMs, were implicated in promoting tumor growth and immune escape, offering potential targets for novel therapeutic interventions.
[METHODS] Single-cell sequencing data from paired GC and normal stomach tissues, obtained from the GEO database (GSE184198), were processed to reveal cellular heterogeneity and identify TAM subsets with high OXPHOS activity. Using the TCGA STAD dataset, survival analyses were conducted on 435 GC patients to establish a high-OXPHOS-macrophage-related prognostic signature.
[RESULTS] We identified eight distinct cell types within the GC TME, indicating significant cellular heterogeneity. Macrophages, particularly TAMs, were found in greater numbers in tumor tissue, with the C3 macrophage subset exhibiting the highest OXPHOS score. A 19-gene high-OXPHOS-macrophage-related prognostic signature was constructed, stratifying patients into different risk categories with significant survival differences (P<0.05). NPC2, LY96, and TPP1 were identified as key macrophage-expressed markers, correlating with prognosis. Cell communication analysis revealed increased interaction in tumor tissues, especially involving NPC2, LY96, and TPP1 positive macrophages, which facilitated tumorigenesis and immune evasion.
[CONCLUSION] The high-OXPHOS-macrophage-related prognostic signature derived from scRNA-seq data provides valuable insights into GC patient stratification. NPC2, LY96, and TPP1, highly expressed in TAMs, were implicated in promoting tumor growth and immune escape, offering potential targets for novel therapeutic interventions.
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