An Immune Checkpoint-Related Gene Signature for Predicting Survival of Pediatric Acute Myeloid Leukemia

Jiang, Feng; Wang, Xinyu; Wang, Mingyan; Mao, Yan Ping; Miao, Xiaolin; Wu, Chuyan; Zhou, Guoping

doi:10.1155/2021/5550116

Cited by 23 publications

(23 citation statements)

References 39 publications

(37 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…and Jiang et al . developed leukaemia stem cell score gene signature and immune checkpoint related gene signature respectively in paediatric AML predictive of survival outcomes(4, 41). None of the above studies evaluated alterations in mitochondrial gene expressions.…”

Section: Discussionmentioning

confidence: 99%

Decoding mitochondrial genes in pediatric AML and development of a novel prognostic mitochondrial gene signature

Chaudhary

Ganguly

Palanichamy

et al. 2022

Preprint

View full text Add to dashboard Cite

Background: Gene expression profile of mitochondrial-related genes is not well deciphered in pediatric acute myeloid leukaemia (AML). We aimed to identify mitochondria-related differentially expressed genes (DEGs) in pediatric AML with their prognostic significance. Methods: Children with de novo AML were included prospectively between July 2016-December 2019. Transcriptomic profiling was done for a subset of samples, stratified by mtDNA copy number. Top mitochondria-related DEGs were identified and validated by real-time PCR. A prognostic gene signature risk score was formulated using DEGs independently predictive of overall survival (OS) in multivariable analysis. Predictive ability of the risk score was estimated along with external validation in The Tumor Genome Atlas (TCGA) AML dataset. Results: In 143 children with AML, twenty mitochondria-related DEGs were selected for validation, of which 16 were found to be significantly dysregulated. Upregulation of SDHC (p<0.001), CLIC1 (p=0.013) and downregulation of SLC25A29 (p<0.001) were independently predictive of inferior OS, and included for developing prognostic risk score. The risk score model was independently predictive of survival over and above ELN risk categorization (Harrell's c-index: 0.675). High-risk patients (risk score above median) had significantly inferior OS (p<0.001) and event free survival (p<0.001); they were associated with poor-risk cytogenetics (p=0.021), ELN intermediate/poor risk group (p=0.016), absence of RUNX1-RUNX1T1 (p=0.027), and not attaining remission (p=0.016). On external validation, the risk score also predicted OS (p=0.019) in TCGA dataset. Conclusion: We identified and validated mitochondria-related DEGs with prognostic impact in pediatric AML and also developed a novel 3-gene based externally validated gene signature predictive of survival.

show abstract

Section: Discussionmentioning

confidence: 99%

Decoding mitochondrial genes in pediatric AML and development of a novel prognostic mitochondrial gene signature

Chaudhary

Ganguly

Palanichamy

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…AML patients can be divided into high-and low-risk groups according to risk score, and we found that the survival was significantly different between the two risk groups. In ROC analysis, the AUC values of 1and 3-year survival were greater than 0.8 in the patients with AML from the TCGA cohort, indicating a superior predictive power in comparison with Zhao et al (2021) (3-year AUC 0.706) and Jiang et al (2021) (3-year AUC 0.711). Notably, risk score was identified as the independent prognostic factor after univariate and multivariate analyses.…”

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). However, the results of these studies were biased because they mainly focus on a small number of genes that were related to special functions instead of the whole gene population.…”

Section: Discussionmentioning

confidence: 99%

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

Wang

Zhuo

Wang

et al. 2022

Front. Cell Dev. Biol.

View full text Add to dashboard Cite

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.

show abstract

“…Jiang’s study predicted the prognosis of pediatric AML patients by immune checkpoint, and the degree of immune cell infiltration calculated in the study was similar to that in our study. ( Jiang et al, 2021 ). Tumor-infiltrating immune cells are highly predictive of tumor progression and patient survival.…”

Section: Discussionmentioning

confidence: 99%

“…Despite the considerable improvements achieved in intensified treatment strategy, supportive care, and risk-adapted patient stratification, the overall survival (OS) does not exceed 70% and relapse rates range between 25% and 35% ( Lonetti et al, 2019 ). AML represents a clinical challenge because of its poor prognosis, highlighting an urgent need to explore novel therapeutic targets and new biomarkers for diagnosis and prognosis ( Jiang et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Analysis of N6-Methyladenosine-Related Long Noncoding RNA Prognosis of Acute Myeloid Leukemia and Immune Cell Infiltration

et al. 2022

View full text Add to dashboard Cite

N6-Methyladenosine-related long noncoding RNAs play an essential role in many cancers’ development. However, the relationship between m6A-related lncRNAs and acute myelogenous leukemia (AML) prognosis remains unclear. We systematically analyzed the association of m6A-related lncRNAs with the prognosis and tumor immune microenvironment (TME) features using the therapeutically applicable research to generate effective treatment (TARGET) database. We screened 315 lncRNAs associated with AML prognosis and identified nine key lncRNAs associated with m6A by the LASSO Cox analysis. A model was established based on these nine lncRNAs and the predictive power was explored in The Cancer Genome Atlas (TCGA) database. The areas under the ROC curve of TARGET and TCGA databases for ROC at 1, 3, and 5 years are 0.701, 0.704, and 0.696, and 0.587, 0.639, and 0.685, respectively. The nomogram and decision curve analysis (DCA) showed that the risk score was more accurate than other clinical indicators in evaluating patients’ prognoses. The clusters with a better prognosis enrich the AML pathways and immune-related pathways. We also found a close correlation between prognostic m6A-related lncRNAs and tumor immune cell infiltration. LAG3 expression at the immune checkpoint was lower in the worse prognostic cluster. In conclusion, m6A-related lncRNAs partly affected AML prognosis by remodeling the TME and affecting the anticarcinogenic ability of immune checkpoints, especially LAG3 inhibitors. The prognostic model constructed with nine key m6A-related lncRNAs can provide a method to assess the prognosis of AML patients in both adults and children.

show abstract

An Immune Checkpoint-Related Gene Signature for Predicting Survival of Pediatric Acute Myeloid Leukemia

Cited by 23 publications

References 39 publications

Decoding mitochondrial genes in pediatric AML and development of a novel prognostic mitochondrial gene signature

Decoding mitochondrial genes in pediatric AML and development of a novel prognostic mitochondrial gene signature

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

Comprehensive Analysis of N6-Methyladenosine-Related Long Noncoding RNA Prognosis of Acute Myeloid Leukemia and Immune Cell Infiltration

Contact Info

Product

Resources

About