Introduction: Tumor-associated macrophages (TAM) play a dual role in the development of gastric cancer (GC). This study aims to analyze the prognostic value of TAM density in GC patients.
Evidence Acquisition: We conducted a meta-analysis of 11 studies (N.=1043) to investigate the correlation between TAM density and the overall survival (OS) or disease free survival (DFS) of GC patients. Pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated by the STATA statistical software.
Evidence Synthesis: The HR of OS of GC patients with high-density TAM is 1.56 (95% CI: 0.90~2.22, P<0.001) as compared with those with low-density TAM, and that of DFS is 1.10 (95% CI: 0.16~2.03, P=0.022), indicating that TAM density does not significantly predict the poor survival of GC. A subgroup analysis by ethnicity also revealed no significance effect between TAM density and a worse OS among both Asians and Caucasians (Asians: HR=1.47, 95% CI: 0.76~2.18, P<0.001; Caucasians: HR=2.23, 95% CI: 0.62~3.84, P=0.007, respectively).
Conclusions: Our findings provide empirical evidence that TAM density is not an independent predictor for the survival of GC patients.
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Cancer Med
January 2025
Medical Data Analytics Centre, The Chinese University of Hong Kong, Hong Kong SAR, China.
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Department of Microbiology, Basic Science Center, Autonomous University of Aguascalientes, Aguascalientes, Mexico.
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School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, 518107, China.
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School of Medicine, South China University of Technology, Guangzhou, 510006, China.
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Sci Rep
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Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, 238 Ziyang Road, Wuhan, 430060, Hubei, People's Republic of China.
The current mortality rates for breast cancer underscore the need for better prognostic tools; moreover, LIM and calponin homology domain 1 (LIMCH1), which is a protein with dual roles in cancer, is a promising candidate for investigation. This study employed an integrative approach combining bioinformatics analysis of The Cancer Genome Atlas (TCGA) cohort and clinical immunohistochemistry (IHC) cohort data. We analysed LIMCH1 expression patterns, its associations with clinicopathological features and prognosis, and its impact on the tumour immune microenvironment (TIME).
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