A Prognostic Autophagy-Related Long Non-coding RNA (ARlncRNA) Signature in Acute Myeloid Leukemia (AML)

Zhuo

et al. 2022

Front. Cell Dev. Biol.

Background: Emerging evidence has proven that ferroptosis plays an important role in the development of acute myeloid leukemia (AML), whereas the exact role of ferroptosis-associated genes in AML patients’ prognosis remained unclear.Materials and Methods: Gene expression profiles and corresponding clinical information of AML cases were obtained from the TCGA (TCGA-LAML), GEO (GSE71014), and TARGET databases (TARGET-AML). Patients in the TCGA cohort were well-grouped into two clusters based on ferroptosis-related genes, and differentially expressed genes were screened between the two clusters. Univariate Cox and LASSO regression analyses were applied to select prognosis-related genes for the construction of a prognostic risk-scoring model. Survival analysis was analyzed by Kaplan–Meier and receiver operator characteristic curves. Furthermore, we explored the correlation of the prognostic risk-scoring model with immune infiltration and chemotherapy response. Risk gene expression level was detected by quantitative reverse transcription polymerase chain reaction.Results: Eighteen signature genes, including ZSCAN4, ASTN1, CCL23, DLL3, EFNB3, FAM155B, FOXL1, HMX2, HRASLS, LGALS1, LHX6, MXRA5, PCDHB12, PRINS, TMEM56, TWIST1, ZFPM2, and ZNF560, were developed to construct a prognostic risk-scoring model. AML patients could be grouped into high- and low-risk groups, and low-risk patients showed better survival than high-risk patients. Area under the curve values of 1, 3, and 5 years were 0.81, 0.827, and 0.786 in the training set, respectively, indicating a good predictive efficacy. In addition, age and risk score were the independent prognostic factors after univariate and multivariate Cox regression analyses. A nomogram containing clinical factors and prognostic risk-scoring model was constructed to better estimate individual survival. Further analyses demonstrated that risk score was associated with the immune infiltration and response to chemotherapy. Our experiment data revealed that LGALS1 and TMEM56 showed notably decreased expression in AML samples than that of the normal samples.Conclusion: Our study shows that the prognostic risk-scoring model and key risk gene may provide potential prognostic biomarkers and therapeutic option for AML patients.

Section: Discussionmentioning

confidence: 93%

“…Current studies identify a ferroptosis-or autophagy-related long noncoding RNA signature for predicting prognosis in the patients with AML (Li R. et al, 2021;Zhao et al, 2021;Zheng et al, 2021). Immune-or immune checkpoint-related gene signatures were also developed and validated in AML patients (Li R. et al, 2021;Jiang et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

Identification and Validation of a Prognostic Risk-Scoring Model Based on Ferroptosis-Associated Cluster in Acute Myeloid Leukemia

Zhuo

et al. 2022

Front. Cell Dev. Biol.

“…Among the lncRNAs in the prognostic signature, USP30-AS1 has been reported to be related to autophagy and immunity in bladder cancer ( Wan et al, 2021 ), cervical cancer ( Chen et al, 2020 ) and melanoma ( Ding et al, 2021 ). MIR133A1HG was also reported to be one of the lncRNAs in the autophagy-related signature for AML ( Zhao et al, 2021 ). However, the underlying molecular biological mechanism has not been elucidated.…”

Section: Discussionmentioning

confidence: 99%

Identification of m6A-Related lncRNAs Associated With Prognoses and Immune Responses in Acute Myeloid Leukemia

Ding

Liang

Cheng

et al. 2021

Front. Cell Dev. Biol.

Background: Acute myeloid leukemia (AML) remains the most common type of hematopoietic malignancy in adults and has an unfavorable outcome. Herein, we aimed to construct an N6-methylandenosine (m6A)-related long noncoding RNAs (lncRNAs) signature to accurately predict the prognosis of patients with AML using the data downloaded from The Cancer Genome Atlas (TCGA) database.Methods: The RNA-seq and clinical data were obtained from the TCGA AML cohort. First, Pearson correlation analysis was performed to identify the m6A-related lncRNAs. Next, univariate Cox regression analysis was used to determine the candidate lncRNAs with prognostic value. Then, feature selection was carried out by Least absolute shrinkage and selection operator (LASSO) analysis, and seven eligible m6A-related lncRNAs were included to construct the prognostic risk signature. Kaplan–Meier and receiver operating characteristic (ROC) curve analyses were performed to evaluate the predictive capacity of the risk signature both in the training and testing datasets. A nomogram was used to predict 1-year, 2-year, and 3-year overall survival (OS) of AML patients. Next, the expression levels of lncRNAs in the signature were validated in AML samples by qRT-PCR. Functional enrichment analyses were carried out to identify probable biological processes and cellular pathways. The ceRNA network was developed to explore the downstream targets and mechanisms of m6A-related lncRNAs in AML.Results: Seven m6A-related lncRNAs were identified as a prognostic signature. The low-risk group hold significantly prolonged OS. The nomogram showed excellent accuracy of the signature for predicting 1-year, 2-year and 3-year OS (AUC = 0.769, 0.820, and 0.800, respectively). Moreover, the risk scores were significantly correlated with enrichment in cancer hallmark- and malignancy-related pathways and immunotherapy response in AML patients.Conclusion: We developed and validated a novel risk signature with m6A-related lncRNAs which could predict prognosis accurately and reflect the immunotherapy response in AML patients.

“…Although the role of DNAJB9 in regulating autophagy to influence chemotherapy resistance is unknown, the SNHG5/miR-32/DNAJB9 axis could be an efficient target for developing modalities to increase chemosensitivity in AML patients. Also, a recent study found that a signature containing four autophagy-related lncRNAs (MIR133A1HG, AL359715.1, MIRLET7BHG, and AL356752.1) has the potential as a biomarker to predict the survival of patients with AML [ 158 ]. Moreover, a preprint version of a study suggested that an autophagy-related lncRNA signature containing six lncRNAs (HYMAI, MIR155HG, MGC12916, DIRC3, C1orf220, and HCP5) has important prognostic value [ 159 ].…”

Section: Introductionmentioning

confidence: 99%

The dual role of autophagy in acute myeloid leukemia

et al. 2022

Acute myeloid leukemia (AML) is a severe hematologic malignancy prevalent in older patients, and the identification of potential therapeutic targets for AML is problematic. Autophagy is a lysosome-dependent catabolic pathway involved in the tumorigenesis and/or treatment of various cancers. Mounting evidence has suggested that autophagy plays a critical role in the initiation and progression of AML and anticancer responses. In this review, we describe recent updates on the multifaceted functions of autophagy linking to genetic alterations of AML. We also summarize the latest evidence for autophagy-related genes as potential prognostic predictors and drivers of AML tumorigenesis. We then discuss the crosstalk between autophagy and tumor cell metabolism into the impact on both AML progression and anti-leukemic treatment. Moreover, a series of autophagy regulators, i.e., the inhibitors and activators, are described as potential therapeutics for AML. Finally, we describe the translation of autophagy-modulating therapeutics into clinical practice. Autophagy in AML is a double-edged sword, necessitating a deeper understanding of how autophagy influences dual functions in AML tumorigenesis and anti-leukemic responses.