Identification of a Prognostic Gene Signature Associated with Microenvironment in Acute Myeloid Leukemia

Abstract Background: Acute myeloid leukemia (AML) is a common hematologic malignancy with poor prognosis. Accumulating reports have indicated that the tumor microenvironment (TME) performs a critical role in the progress of the disease and the clinical outcomes of patients. To date, the role of TME in AML remains clouded due to the complex regulatory mechanisms in it. In this study, We identified key prognostic genes relate to TME in AML and developed a novel gene signature for individualized prognosis assessment. Methods: The expression profiles of AML samples with clinical information were obtained from the Cancer Genome Atlas (TCGA). The ESTIMATE algorithm was applied to calculate the TME relevant immune and stromal scores. The differentially expressed genes (DEGs) were selected based on the immune and stromal scores. Then, the survival analysis was applied to select prognostic DEGs, and these genes were annotated by functional enrichment analysis. A TME relevant gene signature with predictive capability was constructed by a series of regression analyses and performed well in another cohort from the Gene Expression Omnibus (GEO) database. Moreover, we also developed a nomogram with the integration of the gene signature and clinical indicators to establish an individually quantified risk-scoring system. Results: In the AML microenvironment, a total of 181 DEGs with prognostic value were clarified. Then a seven-gene ( IL1R2, MX1, S100A4, GNGT2, ZSCAN23, PLXNB1 and DPY19L2 ) signature with robust prediction was identified, and was validated by an independent cohort of AML samples from the GSE71014. Gene set enrichment analysis (GSEA) of genes in the gene signature revealed these genes mainly enriched in the immune and inflammatory related processes. The correlation between the signature-calculated risk scores and the clinical features indicated that patients with high risk scores were accompanied by adverse survival. Finally, a nomogram with clinical utility was constructed. Conclusion: Our study explored and identified a novel TME relevant seven-gene signature, which could serve as a prognostic indicator for AML. Meanwhile, we also establish a nomogram with clinical significance. These findings might provide new insights into the diagnosis, treatment and prognosis of AML.

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TET2/IDH1/2/WT1 and NPM1 Mutations Influence the RUNX1 Expression Correlations in Acute Myeloid Leukemia

Medicina ◽

10.3390/medicina56120637 ◽

2020 ◽

Vol 56 (12) ◽

pp. 637

Author(s):

Sergiu Pasca ◽

Ancuta Jurj ◽

Ciprian Tomuleasa ◽

Mihnea Zdrenghea

Keyword(s):

Acute Myeloid Leukemia ◽

Myeloid Leukemia ◽

Mutational Analysis ◽

Expression Profiles ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Runx1 Expression ◽

Acute Myeloid

Background and objectives: Mutational analysis has led to a better understanding of acute myeloid leukemia (AML) biology and to an improvement in clinical management. Some of the most important mutations that affect AML biology are represented by mutations in genes related to methylation, more specifically: TET2, IDH1, IDH2 and WT1. Because it has been shown in numerous studies that mutations in these genes lead to similar expression profiles and phenotypes in AML, we decided to assess if mutations in any of those genes interact with other genes important for AML. Materials and Methods: We downloaded the clinical data, mutational profile and expression profile from the TCGA LAML dataset via cBioPortal. Data were analyzed using classical statistical methods and functional enrichment analysis software represented by STRING and GOrilla. Results: The first step we took was to assess the 196 AML cases that had a mutational profile available and observe the mutations that overlapped with TET2/IDH1/2/WT1 mutations. We observed that RUNX1 mutations significantly overlap with TET2/IDH1/2/WT1 mutations. Because of this, we decided to further investigate the role of RUNX1 mutations in modulating the level of RUNX1 mRNA and observed that RUNX1 mutant cases presented higher levels of RUNX1 mRNA. Because there were only 16 cases of RUNX1 mutant samples and that mutations in this gene determined a change in mRNA expression, we further observed the correlation between RUNX1 and other mRNAs in subgroups regarding the presence of hypermethylating mutations and NPM1. Here, we observed that both TET2/IDH1/2/WT1 and NPM1 mutations increase the number of genes negatively correlated with RUNX1 and that these genes were significantly linked to myeloid activation. Conclusions: In the current study, we have shown that NPM1 and TET2/IDH1/2/WT1 mutations increase the number of negative correlations of RUNX1 with other transcripts involved in myeloid differentiation.

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Characterization of somatic mutation-associated microenvironment signatures in acute myeloid leukemia patients based on TCGA analysis

Scientific Reports ◽

10.1038/s41598-020-76048-8 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Jun Wang ◽

Feng-Ting Dao ◽

Lu Yang ◽

Ya-Zhen Qin

Keyword(s):

Gene Expression ◽

Acute Myeloid Leukemia ◽

Risk Stratification ◽

Myeloid Leukemia ◽

Expression Profiles ◽

Critical Role ◽

Genetic Mutation ◽

Functional Enrichment ◽

Genetic Mutations ◽

Acute Myeloid

Abstract Recurrent genetic mutations occur in acute myeloid leukemia (AML) and have been incorporated into risk stratification to predict the prognoses of AML patients. The bone marrow microenvironment plays a critical role in the development and progression of AML. However, the characteristics of the genetic mutation-associated microenvironment have not been comprehensively identified to date. In this study, we obtained the gene expression profiles of 173 AML patients from The Cancer Genome Atlas (TCGA) database and calculated their immune and stromal scores by applying the ESTIMATE algorithm. Immune scores were significantly associated with OS and cytogenetic risk. Next, we categorized the intermediate and poor cytogenetic risk patients into individual-mutation and wild-type groups according to RUNX1, ASXL1, TP53, FLT3-ITD, NPM1 and biallelic CEBPA mutation status. The relationships between the immune microenvironment and each genetic mutation were investigated by identifying differentially expressed genes (DEGs) and conducting functional enrichment analyses of them. Significant immune- and stromal-relevant DEGs associated with each mutation were identified, and most of the DEGs (from the FLT3-ITD, NPM1 and biallelic CEBPA mutation groups) were validated in the GSE14468 cohort downloaded from the Gene Expression Omnibus (GEO) database. In summary, we identified key immune- and stromal-relevant gene signatures associated with genetic mutations in AML, which may provide new biomarkers for risk stratification and personalized immunotherapy.

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Identification of Seven Novel Ferroptosis-Related Long Non - Coding RNA Signatures as a Diagnostic Biomarker for Acute Myeloid Leukemia

10.21203/rs.3.rs-502041/v1 ◽

2021 ◽

Author(s):

Zhiyuan Zheng ◽

Wei Wu ◽

Zehang Lin ◽

Shuhan Liu ◽

Qiaoqian Chen ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Risk Score ◽

Myeloid Leukemia ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Gene Set ◽

Kaplan Meier ◽

Acute Myeloid

Abstract Background: Ferroptosis is a newly discovered type of programmed cell death that participates in the biological processes of various cancers. However, the mechanism by which ferroptosis modulates acute myeloid leukemia (AML) remains unclear. This study aimed to investigate the role of ferroptosis-related long non-coding RNAs (lncRNAs) in AML and establish a corresponding prognostic model.Methods: RNA-sequencing data and clinicopathological characteristics were obtained from The Cancer Genome Atlas database, and ferroptosis-related genes were obtained from the FerrDb database. The “limma” R package, Cox regression, and the least absolute shrinkage and selection operator were used to determine the ferroptosis-related lncRNA signature with the lowest Akaike information criteria (AIC). The risk score of ferroptosis-related lncRNAs was calculated and patients with AML were divided into high- and low-risk groups based on the median risk score. The Kaplan-Meier curve and Cox regression were used to evaluate the prognostic value of the risk score. Finally, gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) were performed to explore the biological functions of the ferroptosis-related lncRNAs.Results: Seven ferroptosis-related lncRNA signatures were identified in the training group, and Kaplan-Meier and Cox regression analyses confirmed that risk scores were independent prognostic predictors of AML in both the training and validation groups (All P < 0.05). In addition, the area under the curve (AUC) analysis confirmed that the signatures had a good predictive ability for the prognosis of AML. GSEA and ssGSEA showed that the seven ferroptosis-related lncRNAs were related to glutathione metabolism and tumor immunity.Conclusions: In this study, seven novel ferroptosis-related lncRNA signatures (AP001266.2, AC133961.1, AF064858.3, AC007383.2, AC008906.1, AC026771.1, and KIF26B-AS1) were established. These signatures were shown to accurately predict the prognosis of AML, which would provide new insights into strategies for the development of new AML therapies.

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Isolation of CD34− and CD34+ Leukemia Stem Cells from Acute Myeloid Leukemia Blasts Using CD200

Blood ◽

10.1182/blood-2018-99-119318 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 2790-2790 ◽

Cited By ~ 1

Author(s):

Jenny M. Ho ◽

Stephanie M. Dobson ◽

Jessica McLeod ◽

Veronique Voisin ◽

Alex Murison ◽

...

Keyword(s):

Stem Cells ◽

Acute Myeloid Leukemia ◽

Myeloid Leukemia ◽

Expression Profiles ◽

Gene Set Enrichment Analysis ◽

Leukemia Stem Cells ◽

Npm1 Mutation ◽

Cd34 Cells ◽

Cd34 Expression ◽

Acute Myeloid

Abstract Therapy resistance and relapse in acute myeloid leukemia (AML) are driven by leukemia stem cells (LSCs). Recent evidence highlighting functional and genetic heterogeneity among LSC subclones underscores the importance of capturing the entire LSC compartment in studies of LSC biology. Although LSCs are often enriched in the CD34+CD38- cell fraction, they are frequently detected in other phenotypic fractions, and in some cases are restricted to the CD34- population. In order to discover novel LSC markers, we examined genes differentially expressed between functionally-validated LSC+ and LSC- cell fractions obtained from primary AML samples, and identified CD200 as a candidate cell surface marker for LSCs. CD200 expression in 57 primary AML samples was analyzed by flow cytometry using anti-human CD200 clone 1B9(kindly provided by Trillium Therapeutics Inc.). CD200 was present on a greater proportion of CD45dim blasts compared to more differentiated CD45high non-blast populations (54.4% versus 21.7%, p<0.0001); CD200+ cells often represented a distinct blast population. Overall there was a positive but non-linear correlation (R2=0.46, p<0.0001) between CD34 and CD200 expression; the proportion of CD200+ blasts was significantly greater than that of CD34+ blasts in samples with low to intermediate CD34 expression. In AMLs where CD34 expression was lower than CD200, CD34 was present on a subset of CD200+ blasts; accordingly, CD200+ blasts comprised variable proportions of CD34- and CD34+ cells. These observations suggest that CD200 expression on blasts could be a better marker for LSCs than CD34. To validate CD200 as a LSC marker, leukemic blasts were sorted from 15 primary AML samples based on CD45 and CD200 expression and transplanted into NSG mice. Samples were selected based on either the presence of both CD200+ and CD200- blasts, or CD200 expression on <5% of mononuclear cells (MNCs). In 8 of 15 AMLs, LSCs were enriched within the CD200+ fraction (termed CD200+ LSCs). In 4 of these cases, LSCs comprised both CD34- and CD34+ cells, but the entire LSC compartment was captured within the CD200+ blast population. Limiting dilution studies showed that CD200 expression enriched for CD200+ LSCs by up to 20-fold. In 6 of the remaining samples, LSCs resided in the CD200- fraction (termed CD200- LSCs), while in one sample, LSCs were present in both CD200+ and CD200- fractions. In AMLs with CD200- LSCs, CD200 was expressed on <5% of MNCs and <5% of blasts, in contrast to AMLs with CD200+ LSCs where CD200 expression on MNCs was variable (3% to 85%) and >5% on blasts. Overall, these results indicate that CD200 expression can be used to segregate LSCs from bulk leukemia cells. CD200 expression may be a particularly useful LSC marker in cytogenetically normal AMLs with NPM1 mutation (CN-AMLNPM1c), which have low or negative CD34 expression and commonly possess CD34- LSCs. Among 20 CN-AMLNPM1c samples, the proportion of CD200+ blasts was higher than that of CD34+ blasts irrespective of FLT3-ITD status, although there was a trend towards higher CD200 expression in FLT3-ITD+ samples. In xenotransplantation assays, 7 of 8 CN-AMLNPM1c samples tested contained CD200+ LSCs while the remaining sample contained both CD200+ and CD200- LSCs. Principal component analysis of gene expression profiles demonstrated that functionally-validated CD200+ LSC-containing fractions from CN-AMLNPM1c patients clustered separately from LSC fractions from NPM1wt or cytogenetically-abnormal cases, and were enriched for stem cell genes by gene set enrichment analysis. Furthermore, ATAC-Seq analysis demonstrated greater chromatin accessibility in CD200+ LSC-containing versus CD200‒ LSC-depleted fractions from CN-AMLNPM1c patients, with unique enrichment of HOX motifs. These data validate CD200 as an LSC marker in CN-AMLNPM1c cases. In summary, CD200 is a valuable tool for capturing heterogeneous LSC populations including both CD34+ and CD34- LSCs in many primary AML samples. It will be particularly useful for future studies of LSCs in CN-AMLNPM1c where CD34 expression does not identify LSCs. Disclosures No relevant conflicts of interest to declare.

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Identification and Development of a Novel 4-Gene Immune-Related Signature to Predict Osteosarcoma Prognosis

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2020.608368 ◽

2020 ◽

Vol 7 ◽

Author(s):

Mingde Cao ◽

Junhui Zhang ◽

Hualiang Xu ◽

Zhujian Lin ◽

Hong Chang ◽

...

Keyword(s):

Risk Model ◽

Cox Regression ◽

Expression Profiles ◽

External Validation ◽

Treatment Strategies ◽

Enrichment Analysis ◽

Gene Signature ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Immune Related Genes

Osteosarcoma (OS) is a malignant disease that develops rapidly and is associated with poor prognosis. Immunotherapy may provide new insights into clinical treatment strategies for OS. The purpose of this study was to identify immune-related genes that could predict OS prognosis. The gene expression profiles and clinical data of 84 OS patients were obtained from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. According to non-negative matrix factorization, two molecular subtypes of immune-related genes, C1 and C2, were acquired, and 597 differentially expressed genes between C1 and C2 were identified. Univariate Cox analysis was performed to get 14 genes associated with survival, and 4 genes (GJA5, APBB1IP, NPC2, and FKBP11) obtained through least absolute shrinkage and selection operator (LASSO)-Cox regression were used to construct a 4-gene signature as a prognostic risk model. The results showed that high FKBP11 expression was correlated with high risk (a risk factor), and that high GJA5, APBB1IP, or NPC2 expression was associated with low risk (protective factors). The testing cohort and entire TARGET cohort were used for internal verification, and the independent GSE21257 cohort was used for external validation. The study suggested that the model we constructed was reliable and performed well in predicting OS risk. The functional enrichment of the signature was studied through gene set enrichment analysis, and it was found that the risk score was related to the immune pathway. In summary, our comprehensive study found that the 4-gene signature could be used to predict OS prognosis, and new biomarkers of great significance for understanding the therapeutic targets of OS were identified.

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Chemoresponse of de novo Acute Myeloid Leukemia to “7+3” Induction can Be Predicted by c-Myc-facilitated Cytogenetics

Frontiers in Pharmacology ◽

10.3389/fphar.2021.649267 ◽

2021 ◽

Vol 12 ◽

Author(s):

Tzu-Hung Hsiao ◽

Ren Ching Wang ◽

Tsai-Jung Lu ◽

Chien-Hung Shih ◽

Yu-Chen Su ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

High Risk ◽

Myeloid Leukemia ◽

De Novo ◽

Enrichment Analysis ◽

Standard Of Care ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Myc Gene ◽

Acute Myeloid

Background: Identifying patients with de novo acute myeloid leukemia (AML) who will probably respond to the “7 + 3” induction regimen remains an unsolved clinical challenge. This study aimed to identify whether c-Myc could facilitate cytogenetics to predict a “7 + 3” induction chemoresponse in de novo AML.Methods: We stratified 75 untreated patients (24 and 51 from prospective and retrospective cohorts, respectively) with de novo AML who completed “7 + 3” induction into groups with and without complete remission (CR). We then compared Myc-associated molecular signatures between the groups in the prospective cohort after gene set enrichment analysis. The expression of c-Myc protein was assessed by immunohistochemical staining. We defined high c-Myc-immunopositivity as > 40% of bone marrow myeloblasts being c-Myc (+).Results: Significantly more Myc gene expression was found in patients who did not achieve CR by “7 + 3” induction than those who did (2439.92 ± 1868.94 vs. 951.60 ± 780.68; p = 0.047). Expression of the Myc gene and c-Myc protein were positively correlated (r = 0.495; p = 0.014). Although the non-CR group did not express more c-Myc protein than the CR group (37.81 ± 25.13% vs. 29.04 ± 19.75%; p = 0.151), c-Myc-immunopositivity could be a surrogate to predict the “7 + 3” induction chemoresponse (specificity: 81.63%). More importantly, c-Myc-immunopositivity facilitated cytogenetics to predict a “7 + 3” induction chemoresponse by increasing specificity from 91.30 to 95.92%.Conclusion: The “7 + 3” induction remains the standard of care for de novo AML patients, especially for those without a high c-Myc-immunopositivity and high-risk cytogenetics. However, different regimens might be considered for patients with high c-Myc-immunopositivity or high-risk cytogenetics.

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

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.770451 ◽

2021 ◽

Vol 9 ◽

Author(s):

Ding Li ◽

Jiaming Liang ◽

Cheng Cheng ◽

Wenbin Guo ◽

Shuolei Li ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Myeloid Leukemia ◽

Cox Regression ◽

Pearson Correlation ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Risk Scores ◽

Hematopoietic Malignancy ◽

Cox Regression Analysis ◽

Acute Myeloid

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.

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Identification of Aberrantly Methylated and Silenced Genes in Acute Myeloid Leukemia by Combined Methylation/expression Analysis

10.21203/rs.3.rs-87795/v1 ◽

2020 ◽

Author(s):

Chao Guo ◽

Qian-qian Ju ◽

Chun-xia Zhang ◽

Ming Gong ◽

Ya-yue Gao ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Subgroup Analysis ◽

Myeloid Leukemia ◽

Prognostic Significance ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Aberrant Methylation ◽

Acute Myeloid

Abstract Background Aberrant genomic methylation plays an important role in pathogenic process of acute myeloid leukemia (AML) by silencing tumor suppressor genes (TSG). While the key aberrantly methylated genes and related pathways have not been well understood yet, which we aimed to reveal by combined analysis of methylation and expression datasets. The prognostic significance was validated by survival analysis derived from TCGA database. Methods Micro-array data of GSE 15061 and GSE58477 were downloaded from Gene Expression Omnibus (GEO) database. The differentially methylated regions (DMR) and differentially expressed genes (DEG) were identified using R program (R 3.6.1). Over-representation analysis was performed to obtain the enriched biological processes and pathways. Cox hazards analysis was employed to select the genes significantly associated with AML survival, using the data derived from the Cancer Genome Atlas (TCGA) database. Subgroup analysis, regarding induction type, was conducted to identify biomarkers for HMA treatment. Furthermore, SYNJ2 associated genome-wide gene/miRNA expression and methylation profile were explored. Results A total of 198 aberrant methylation related underexpressed genes were identified. Univariable analysis revealed methylation level of 6 out of 198 genes (CORO1A/MPO/SYNJ2/EHD1/GAS2L1/SLC11A1) were significantly associated with AML survival. SYNJ2 methylation was an independent predictor for OS. Notably, subgroup analysis revealed hypermethylation of CORO1A predicted better OS in HMA group. Further gene set enrichment analysis indicated SYNJ2-associated activation of PI3K-Akt/NF-kappaB/JAK-STAT signaling and checkpoint pathway. The microRNAs, such as miR217/miR485-3p/miR-889-3p, were downregulated in SYNJ2-hypermethylated group, leading to potential HOXA13 upregulation. Conclusion The prognostic methylation signature was revealed in our studies, and SYNJ2 was proved as an independent prognostic factor. Methylation of CORO1A may serve as biomarker for HMA treatment in AML.

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Comprehensive bioinformatic analysis of the expression and prognostic significance of TSC22D domain family genes in acute myeloid leukemia

10.21203/rs.3.rs-1209284/v1 ◽

2022 ◽

Author(s):

XiaoQiang Xu ◽

Xin Jin ◽

JiaXi Wang ◽

Rui Sun ◽

Meng Zhang ◽

...

Keyword(s):

Gene Ontology ◽

Acute Myeloid Leukemia ◽

Therapeutic Target ◽

Myeloid Leukemia ◽

Expression Profiles ◽

Prognostic Significance ◽

Functional Enrichment ◽

Domain Family ◽

Gene Regulatory ◽

Acute Myeloid

Abstract Background: TSC22D domain family genes, including Tsc22d1-4, have been extensively reported to be involved in tumors. However, their expression profiles and prognostic significance in acute myeloid leukemia (AML) remain unknown. Methods: The present study investigated the expression profiles and prognostic significance of TSC22D domain family genes in AML through the use of multiple online databases, including the CCLE, EMBL-EBI, HPA, Oncomine,GEPIA2, UALCAN, BloodSpot, and GSCALite databases. The cBioPortal and GSCALite databases were used to explore the genetic alteration and copy number variation (CNV) of the Tsc22d3 gene. The TRRUST (Version 2) database was used to explore the gene ontology biological process, disease ontology, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with the Tsc22d3 gene. The AnimalTFDB3.0, STRING, and Harmonizome databases were used to investigate the protein–protein interaction (PPI) network of the Tsc22d3 gene. The Harmonizome database was used for Tsc22d3 gene regulatory kinase analysis. The TargetScanHuman 7.2, MiRDB, and ENCORI databases were used to execute the analysis of the Tsc22d3 gene regulatory miRNAs. Then, the GSCALite and GEPIA2021 databases were used to investigate the correlation between Tsc22d3 expression and immune infiltration. Results: The expression of the Tsc22d3 gene was upregulated markedly in AML cells relative to normal hematopoietic stem cells. The expression of the Tsc22d3 gene was increased in AML tumor samples compared with healthy bone marrow samples. And overexpression of the Tsc22d3 gene was associated with poor OS in AML patients.This study implied that the Tsc22d3 gene is a new biomarker for predicting the prognosis of AML. Furthermore, gene ontology analysis showed that Tsc22d3 was involved in leukemia. Functional enrichment analysis showed that the Tsc22d3 gene has many biological functions, including the regulation of many genes, kinases, miRNAs, signaling pathways, and immune infiltration.Therefore, this study suggests that the Tsc22d3 gene may be a potential therapeutic target for AML. Conclusions: Tsc22d3 gene expression was upregulated in AML, and overexpression was associated with poor OS in AML patients. Therefore, the Tsc22d3 gene may serve as a novel prognostic biomarker and therapeutic target for AML.

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Identification of seven novel ferroptosis-related long non-coding RNA signatures as a diagnostic biomarker for acute myeloid leukemia

BMC Medical Genomics ◽

10.1186/s12920-021-01085-9 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Zhiyuan Zheng ◽

Wei Wu ◽

Zehang Lin ◽

Shuhan Liu ◽

Qiaoqian Chen ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Risk Score ◽

Myeloid Leukemia ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Gene Set ◽

Kaplan Meier ◽

Acute Myeloid

Abstract Background Ferroptosis is a newly discovered type of programmed cell death that participates in the biological processes of various cancers. However, the mechanism by which ferroptosis modulates acute myeloid leukemia (AML) remains unclear. This study aimed to investigate the role of ferroptosis-related long non-coding RNAs (lncRNAs) in AML and establish a corresponding prognostic model. Methods RNA-sequencing data and clinicopathological characteristics were obtained from The Cancer Genome Atlas database, and ferroptosis-related genes were obtained from the FerrDb database. The “limma” R package, Cox regression, and the least absolute shrinkage and selection operator were used to determine the ferroptosis-related lncRNA signature with the lowest Akaike information criteria (AIC). The risk score of ferroptosis-related lncRNAs was calculated and patients with AML were divided into high- and low-risk groups based on the median risk score. The Kaplan–Meier curve and Cox regression were used to evaluate the prognostic value of the risk score. Finally, gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) were performed to explore the biological functions of the ferroptosis-related lncRNAs. Results Seven ferroptosis-related lncRNA signatures were identified in the training group, and Kaplan–Meier and Cox regression analyses confirmed that risk scores were independent prognostic predictors of AML in both the training and validation groups (All P < 0.05). In addition, the area under the curve (AUC) analysis confirmed that the signatures had a good predictive ability for the prognosis of AML. GSEA and ssGSEA showed that the seven ferroptosis-related lncRNAs were related to glutathione metabolism and tumor immunity. Conclusions In this study, seven novel ferroptosis-related lncRNA signatures (AP001266.2, AC133961.1, AF064858.3, AC007383.2, AC008906.1, AC026771.1, and KIF26B-AS1) were established. These signatures were shown to accurately predict the prognosis of AML, which would provide new insights into strategies for the development of new AML therapies.

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