Development and validation of a novel survival model for acute myeloid leukemia based on autophagy-related genes

Abstract

Background Acute myeloid leukemia (AML) is one of the most common blood cancers, and is characterized by impaired hematopoietic function and bone marrow (BM) failure. Under normal circumstances, autophagy may suppress tumorigenesis, however under the stressful conditions of late stage tumor growth autophagy actually protects tumor cells, so inhibiting autophagy in these cases also inhibits tumor growth and promotes tumor cell death. Methods AML gene expression profile data and corresponding clinical data were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, from which prognostic-related genes were screened to construct a risk score model through LASSO and univariate and multivariate Cox analyses. Then the model was verified in the TCGA cohort and GEO cohorts. In addition, we also analyzed the relationship between autophagy genes and immune infiltrating cells and therapeutic drugs. Results We built a model containing 10 autophagy-related genes to predict the survival of AML patients by dividing them into high- or low-risk subgroups. The high-risk subgroup was prone to a poorer prognosis in both the training TCGA-LAML cohort and the validation GSE37642 cohort. Univariate and multivariate Cox analysis revealed that the risk score of the autophagy model can be used as an independent prognostic factor. The high-risk subgroup had not only higher fractions of CD4 naïve T cell, NK cell activated, and resting mast cells but also higher expression of immune checkpoint genes CTLA4 and CD274. Last, we screened drug sensitivity between high- and low-risk subgroups. Conclusion The risk score model based on 10 autophagy-related genes can serve as an effective prognostic predictor for AML patients and may guide for patient stratification for immunotherapies and drugs.

Deconvolution of tumor composition using partially available DNA methylation data

“…In contrast, LAML patients with a high infiltration level of NK cells had poorer overall survival than those with a low infiltration level ( p = 0.0449, Fig. 6 D), which was consistent with the study's results [ 44 ] that the NK cells activated with high expression were associated with a poor prognosis. In addition, we also found that several unknown cell types had an impact on the survival of cancer patients (Fig.…”

The clinical significance of integrin subunit alpha V in cancers: from small cell lung carcinoma to pan-cancer

“…All mRNA expression-associated data were transformed by log 2 (x + 1). Datasets with the same platform (e.g., GSE32036 and GSE4127 from GPL6884) were merged for a combined dataset after eliminating batch effects [13][14][15][16], which was similar to the published study [12].…”

“…To detect associations between ITGAV expression and tumor immune microenvironment (TME), the relationship between ITGAV expression and immune infiltration levels (using Pearson coefficient) was explored based on the ESTIMATE algorithm [19,[21][22][23] and CIBERSORT algorithm [14,24,25]. Immune checkpoints were promising in the treatment of cancers [26], and thus, the study also evaluated their associations with ITGAV expression to preliminarily assess the immunotherapy potential of ITGAV in SCLC.…”

The dual role of autophagy in acute myeloid leukemia

“…Decreased Beclin-1 and p62 levels are associated with unfavorable outcomes of AML [ 135 ], suggesting the potential of autophagy genes as biomarkers for hematologic tumors. Although the evidence is inadequate, studies have supported the mediation of AML tumorigenesis by the bioinformatic tools through prediction of risk scoring based on autophagy gene signatures [ 136 , 137 ]. In addition, profiling of genome-wide alternative splicing (AS) events in the AML cohort of The Cancer Genome Atlas indicates that survival-related AS events are enriched in leukemia-associated gene sets, including the autophagy pathway [ 138 , 139 ].…”

“…Univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression identified a six-gene signature ( CASP3, CHAF1B, KLHL24, OPTN, VEGFA, and VPS37C ) predictive of AML progression and survival [ 137 ]. A recent bioinformatics study using 10 ATGs for prediction of AML prognosis showed that groups at high risk of AML have higher expression of immune checkpoint genes and a greater proportion of CD4 T and NK cells [ 136 ]. According to univariate Cox regression analysis of the transcriptomic profiles of patients with AML, 32 ATGs were significantly associated with OS.…”