Identifying a novel 5-gene signature predicting clinical outcomes in acute myeloid leukemia

Sha, Keya; Lu, Ying; Zhang, P.; Pei, Renzhi; Shi, Xiaoyan; Fan, Zhining; Chen, L.

doi:10.1007/s12094-020-02460-1

Cited by 15 publications

(21 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Despite the initial observation of upregulated PGE 2 pathway components in murine leukemia [13], we could not associate prognostic value to PTGS, PTGES, and PTGER in human AML (Figure S4). Instead, only increased PLA2G4A expression predicted adverse outcome (Figure 6B), which was also independently confirmed [39,40]. This is in line with the already described oncogenic properties of PLA2G4A in various cancers [34,[60][61][62], and supports the functional and prognostic value of PLA2G4A in AML that warrants further investigations.…”

Section: Discussionsupporting

confidence: 84%

“…Thus, we interrogated the TCGA data set for a potential correlation between PLA2G4A expression level and survival. In accordance with recently published studies, PLA2G4A correlated with unfavorable prognosis [39,40]. We used median PLA2G4A gene expression for stratification, which demonstrated significantly poorer prognosis regarding disease-free survival (9.6 vs. 32.2 months; p < 0.0001) and overall survival (12.2 vs. 46.7 months; p < 0.0001) in patients with high PLA2G4A expression compared to individuals with low PLA2G4A expression (Figure 6C).…”

Section: Pla2g4a Serves As a Prognostic Marker In Human Amlsupporting

confidence: 76%

See 1 more Smart Citation

A Multiplex CRISPR-Screen Identifies PLA2G4A as Prognostic Marker and Druggable Target for HOXA9 and MEIS1 Dependent AML

Hassan

Lieske

Dörpmund

et al. 2021

IJMS

View full text Add to dashboard Cite

HOXA9 and MEIS1 are frequently upregulated in acute myeloid leukemia (AML), including those with MLL-rearrangement. Because of their pivotal role in hemostasis, HOXA9 and MEIS1 appear non-druggable. We, thus, interrogated gene expression data of pre-leukemic (overexpressing Hoxa9) and leukemogenic (overexpressing Hoxa9 and Meis1; H9M) murine cell lines to identify cancer vulnerabilities. Through gene expression analysis and gene set enrichment analyses, we compiled a list of 15 candidates for functional validation. Using a novel lentiviral multiplexing approach, we selected and tested highly active sgRNAs to knockout candidate genes by CRISPR/Cas9, and subsequently identified a H9M cell growth dependency on the cytosolic phospholipase A2 (PLA2G4A). Similar results were obtained by shRNA-mediated suppression of Pla2g4a. Remarkably, pharmacologic inhibition of PLA2G4A with arachidonyl trifluoromethyl ketone (AACOCF3) accelerated the loss of H9M cells in bulk cultures. Additionally, AACOCF3 treatment of H9M cells reduced colony numbers and colony sizes in methylcellulose. Moreover, AACOCF3 was highly active in human AML with MLL rearrangement, in which PLA2G4A was significantly higher expressed than in AML patients without MLL rearrangement, and is sufficient as an independent prognostic marker. Our work, thus, identifies PLA2G4A as a prognostic marker and potential therapeutic target for H9M-dependent AML with MLL-rearrangement.

show abstract

Section: Discussionsupporting

confidence: 84%

Section: Pla2g4a Serves As a Prognostic Marker In Human Amlsupporting

confidence: 76%

A Multiplex CRISPR-Screen Identifies PLA2G4A as Prognostic Marker and Druggable Target for HOXA9 and MEIS1 Dependent AML

Hassan

Lieske

Dörpmund

et al. 2021

IJMS

View full text Add to dashboard Cite

show abstract

“…We followed the methods of Lai et al and Sha et al to perform the survival analyses [14,15]. In brief, AML patients were grouped into two subgroups, including high and low expression groups, according to the cutoff values determined by the pROC package [16].…”

Section: Survival Analysesmentioning

confidence: 99%

Novel prognostic genes and subclasses of acute myeloid leukemia revealed by survival analysis of gene expression data

et al. 2021

View full text Add to dashboard Cite

Background Acute myeloid leukemia (AML) is biologically heterogeneous diseases with adverse prognosis. This study was conducted to find prognostic biomarkers that could effectively classify AML patients and provide guidance for treatment decision making. Methods Weighted gene co-expression network analysis was applied to detect co-expression modules and analyze their relationship with clinicopathologic characteristics using RNA sequencing data from The Cancer Genome Atlas database. The associations of gene expression with patients’ mortality were investigated by a variety of statistical methods and validated in an independent dataset of 405 AML patients. A risk score formula was created based on a linear combination of five gene expression levels. Results The weighted gene co-expression network analysis detected 63 co-expression modules. The pink and darkred modules were negatively significantly correlated with overall survival of AML patients. High expression of FNDC3B, VSTM1 and CALR was associated with favourable overall survival, while high expression of PLA2G4A was associated with adverse overall survival. Hierarchical clustering analysis of FNDC3B, VSTM1, PLA2G4A, GOLGA3 and CALR uncovered four subgroups of AML patients. The cluster1 AML patients showed younger age, lower cytogenetics risk, higher frequency of NPM1 mutations and more favourable overall survival than cluster3 patients. The risk score was demonstrated to be an indicator of adverse prognosis in AML patients Conclusions The FNDC3B, VSTM1, PLA2G4A, GOLGA3, CALR and risk score may serve as key prognostic biomarkers for the stratification and ultimately guide rational treatment of AML patients.

show abstract

“…Establishment and validation of the 16-gene score We followed Lai et al's methods (14) to choose the set of genes which performed best in prognosis prediction and develop the 16-gene risk score. In brief, the least absolute shrinkage and selection operator (LASSO) models comprising different number of genes were evaluated for prediction accuracies of OS using glmnet in the TCGA dataset (15).…”

Section: Identi Cation Of Survival-related Clinical Features and Genesmentioning

confidence: 99%

Identification and Validation of a Novel 16-Gene Prognostic Signature for Patients with Breast Cancer

Zhong¹,

Jiang²,

Zhang³

et al. 2021

Preprint

View full text Add to dashboard Cite

Background: Despite increased early diagnosis and improved treatment in breast cancer (BRCA) patients, prognosis prediction is still a challenging task due to the disease heterogeneity. This study was to identify a novel gene signature that can accurately evaluate BRCA patient survival. Methods: The gene expression and clinical data of BRCA patients were collected from The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of BRCA International Consortium (METABRIC) databases. Genes associated with prognosis were determined by Kaplan–Meier survival analysis and multivariate Cox regression analysis. A prognostic 16-gene score was established with linear combination of 16 genes. The prognostic value of the signature was validated in the METABRIC dataset. Gene expression analysis was performed to investigate the diagnostic values of 16 genes. Results: The 16-gene score was associated with shortened overall survival in BRCA patients independently of clinicopathological characteristics. The signalling pathways of cell cycle, oocyte meiosis, RNA degradation, progesterone mediated oocyte maturation and DNA replication were the top five most enriched pathways in the high 16-gene score group. The 16-gene nomogram incorporating the survival‐related clinical factors showed improved prediction accuracies for 1-year, 3-year and 5‐year survival (area under curve [AUC] = 0.91, 0.79 and 0.77 respectively). MORN3, IGJ, DERL1 exhibited high accuracy in differentiating BRCA tissues from normal breast tissues (AUC > 0.80 for all cases). Conclusions: The 16-gene profile provides novel insights into the identification of BRCA with a high risk of death, which eventually guides treatment decision making.

show abstract

Identifying a novel 5-gene signature predicting clinical outcomes in acute myeloid leukemia

Cited by 15 publications

References 23 publications

A Multiplex CRISPR-Screen Identifies PLA2G4A as Prognostic Marker and Druggable Target for HOXA9 and MEIS1 Dependent AML

A Multiplex CRISPR-Screen Identifies PLA2G4A as Prognostic Marker and Druggable Target for HOXA9 and MEIS1 Dependent AML

Novel prognostic genes and subclasses of acute myeloid leukemia revealed by survival analysis of gene expression data

Identification and Validation of a Novel 16-Gene Prognostic Signature for Patients with Breast Cancer

Contact Info

Product

Resources

About