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PURPOSE: To identify and validate the immune-related gene signature in patients with acute myeloid leukemia (AML). METHODS: Differentially expressed genes (DEGs) profiles and survival data were obtained from The Cancer Genome Atlas (TCGA), following screened immune-associated genes from the InnateDB database. Subsequently, the weighted gene co-expression network analysis (WGCNA) was used to detect functional modules, and survival analysis was performed. The least absolute shrinkage and selection operator (LASSO) regression model combined with a partial likelihood-based Cox proportional hazard regression model was applied to select prognostic genes, and the ESTIMATE algorithm was used to construct an immune score-based risk assessment model. Finally, two independent datasets from the Gene Expression Omnibus (GEO) and our clinical data were used for external validation. Moreover, a subpopulation of the immune microenvironment cells was analyzed by the CIBERSORT algorithm, and its related serum indicator was identified by the enzyme-linked immunosorbent assay (ELISA) in clinical samples. RESULTS: Finally, CTSD, GNB2, CDK6, and WAS were identified as the immune-related gene signature, and the risk stratification model was validated in both the GSE12417 database and our clinical cohort. Furthermore, the fraction of activated mast cells was identified. CIBERSORT algorithm showed that these cells have a positive association with prognosis. In addition, mast cell stimulator IL-33 was markedly decreased in AML patients with poor prognoses. CONCLUSION: A novel immune-related gene signature (CTSD, GNB2, CDK6 and WAS) and its associated plasma indicator (mast cells activator, IL-33) were found to have prognostic value in AML patients.
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PURPOSE: To explore the clinical significance of plasma pyruvate kinase M2 (PKM2) in assessing the incidence and prognosis of acute leukemia. METHODS: Plasma samples from 56 acute myeloid leukemia (AML) patients, 40 acute lymphoblastic leukemia (ALL) patients, and 66 plasma samples from healthy individuals were collected. The level of plasma PKM2 was detected by enzyme-linked immunosorbent assay. The clinical significance of PKM2 in acute leukemia was assessed by analyzing receiver operating characteristic and survival curves. RESULTS: The plasma levels of PKM2 in AML or ALL patients were significantly higher than those in healthy individuals, respectively. PKM2 can be used as a potential diagnostic index with the AUC of 0.827 for AML and 0.837 for ALL. The level of plasma PKM2 in ALL patients with a BCR/ABL-positive genotype was significantly higher than that in patients with a BCR/ABL-negative genotype (p<0.05). The event-free survival and the overall survival of acute leukemia patients with higher PKM2 expression was worse than those with lower PKM2 expression. CONCLUSION: This study showed that higher levels of PKM2 was negatively correlated with the prognosis of acute leukemia. Therefore, PKM2 can be used as a potential index to assess the incidence and prognosis of acute leukemia.
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BACKGROUND: Skeletal muscle depletion is a prognostic factor in patients with cancer. Here, we evaluated the association between the skeletal muscle index (SMI) and local and systemic responses in patients with colon cancer. PATIENTS AND METHODS: We analyzed the relationships of the SMI with neutrophil, lymphocyte, monocyte, and platelet counts; the neutrophil-to-lymphocyte ratio; albumin levels; and C-reactive protein levels in a cohort of 561 patients, and with the circulating levels of 39 cytokines in a cohort of 125 patients. We also studied the association between the SMI and tumor local inflammatory response and the effect of SMI on survival. RESULTS: The median SMIs for male and female subjects were 44.1 and 34.2 cm2/m2, respectively. We observed positive correlations of the SMI with neutrophil (p=0.022), lymphocyte (p=0.001), and monocyte counts (p=0.003). A low SMI correlated significantly with an increased platelet count (p=0.017), decreased albumin level (p=0.006), neutrophil-to-lymphocyte ratio >3 (p=0.021), and an increased interferon γ-induced protein 10 level (IP-10, r = -0.276, p=0.002). The SMI did not correlate significantly with local inflammatory reactions or the C-reactive protein level. Finally, the SMI was a significant prognosticator in patients with stage III colon cancer (3-year disease-free survival rates: 35.1% for the low SMI arms versus 46.0% in the high SMI arms; HR =2.036; p=0.034). CONCLUSION: This study highlights the association of a low SMI with a high systematic inflammatory response and IP-10 levels. Furthermore, low SMI is a predictor of poor disease-free survival in patients with stage III colon cancer.
