Weighted Gene Coexpression Network Analysis Identifies Cysteine-Rich Intestinal Protein 1 (CRIP1) as a Prognostic Gene Associated with Relapse in Patients with Acute Myeloid Leukemia

Identification of two key biomarkers CD93 and FGL2 associated with survival of acute myeloid leukaemia by weighted gene co-expression network analysis

Acute myeloid leukaemia (AML) is a biologically heterogeneous haematological malignancy. This study was performed to identify the potential biomarkers for the prognosis and treatment of AML. We applied weighted gene co-expression network analysis to identify key modules and hub genes related to the prognosis of AML using data from The Cancer Genome Atlas (TCGA). In total, 1581 differentially expressed genes (1096 upregulated and 485 downregulated) were identified between AML patients and healthy controls, with the blue module being the most significant among 14 modules associated with AML morphology. Through functional enrichment analysis, we identified 217 genes in the blue module significantly enriched in 'neutrophil degranulation' and 'neutrophil activation involved in immune response' pathways. The survival analysis revealed six genes (S100A9, S100A8, HK3, CD93, CXCR2 and FGL2) located in the significantly enriched pathway that were notably related to AML survival. We validated the expression of these six genes at gene and single-cell levels and identified methylation loci of each gene, except for S100A8. Finally, in vitro experiments were performed to demonstrate whether the identified hub genes were associated with AML survival. After knockdown of CD93 and FGL2, cell proliferation was significantly reduced in U937 cell line over 5 days. In summary, we identified CD93 and FGL2 as key hub genes related to AML survival, with FGL2 being a novel biomarker for the prognosis and treatment of AML.

Vacuolar ATPase Is a Possible Therapeutic Target in Acute Myeloid Leukemia: Focus on Patient Heterogeneity and Treatment Toxicity

Vacuolar ATPase (V-ATPase) is regarded as a possible target in cancer treatment. It is expressed in primary acute myeloid leukemia cells (AML), but the expression varies between patients and is highest for patients with a favorable prognosis after intensive chemotherapy. We therefore investigated the functional effects of two V-ATPase inhibitors (bafilomycin A1, concanamycin A) for primary AML cells derived from 80 consecutive patients. The V-ATPase inhibitors showed dose-dependent antiproliferative and proapoptotic effects that varied considerably between patients. A proteomic comparison of primary AML cells showing weak versus strong antiproliferative effects of V-ATPase inhibition showed a differential expression of proteins involved in intracellular transport/cytoskeleton functions, and an equivalent phosphoproteomic comparison showed a differential expression of proteins that regulate RNA processing/function together with increased activity of casein kinase 2. Patients with secondary AML, i.e., a heterogeneous subset with generally adverse prognosis and previous cytotoxic therapy, myeloproliferative neoplasia or myelodysplastic syndrome, were characterized by a strong antiproliferative effect of V-ATPase inhibition and also by a specific mRNA expression profile of V-ATPase interactome proteins. Furthermore, the V-ATPase inhibition altered the constitutive extracellular release of several soluble mediators (e.g., chemokines, interleukins, proteases, protease inhibitors), and increased mediator levels in the presence of AML-supporting bone marrow mesenchymal stem cells was then observed, especially for patients with secondary AML. Finally, animal studies suggested that the V-ATPase inhibitor bafilomycin had limited toxicity, even when combined with cytarabine. To conclude, V-ATPase inhibition has antileukemic effects in AML, but this effect varies between patients.

CRIP1 supports the growth and migration of AML-M5 subtype cells by activating Wnt/β-catenin pathway

Acute myeloid leukemia (AML) is a clinically and molecularly heterogeneous hematopoietic disorder. To effectively eradicate AML, it is urgent to develop new therapeutic approaches and identify novel molecular targets. In silico analysis indicated that the expression of cysteine-rich intestinal protein 1 (CRIP1) was significantly elevated in AML cells and correlated with worse overall survival of the AML patients. However, its specific roles in AML remain elusive. Here we demonstrated that CRIP1 acted as a key oncogene to support AML cell survival and migration. Using a loss-of-function analysis, we found that CRIP1 silencing in U937 and THP1 cells by lentivirus-mediated shRNAs resulted in a decrease in cell growth, migration and colony formation, and an increase in chemosensitivity to Ara-C. CRIP1 silencing induced cell apoptosis and G1/S transition arrest. Mechanically, CRIP1 silencing caused inactivation of Wnt/β-catenin pathway through upregulating axin1 protein. The Wnt/β-catenin agonist SKL2001 markedly rescued the cell growth and migration defect induced by CRIP1 silencing. Our findings reveals that CRIP1 may contribute to AML-M5 pathogenesis and represent a novel target for AML-M5 treatment.

Weighted gene co-expression network analysis identifies key hub genes and pathways in acute myeloid leukemia

Introduction: Acute myeloid leukemia (AML) is the most common type of leukemia in adults. However, there is a gap in understanding the molecular basis of the disease, partly because key genes associated with AML have not been extensively explored. In the current study, we aimed to identify genes that have strong association with AML based on a cross-species integrative approach. Methods: We used Weighted Gene Co-Expression Network Analysis (WGCNA) to identify co-expressed gene modules significantly correlated with human AML, and further selected the genes exhibiting a significant difference in expression between AML and healthy mouse. Protein-protein interactions, transcription factors, gene function, genetic regulation, and coding sequence variants were integrated to identify key hub genes in AML. Results: The cross-species approach identified a total of 412 genes associated with both human and mouse AML. Enrichment analysis confirmed an association of these genes with hematopoietic and immune-related functions, phenotypes, processes, and pathways. Further, the integrated analysis approach identified a set of important module genes including Nfe2, Trim27, Mef2c, Ets1, Tal1, Foxo1, and Gata1 in AML. Six of these genes (except ETS1) showed significant differential expression between human AML and healthy samples in an independent microarray dataset. All of these genes are known to be involved in immune/hematopoietic functions, and in transcriptional regulation. In addition, Nfe2, Trim27, Mef2c, and Ets1 harbor coding sequence variants, whereas Nfe2 and Trim27 are cis-regulated, making them attractive candidates for validation. Furthermore, subtype-specific analysis of the hub genes in human AML indicated high expression of NFE2 across all the subtypes (M0 through M7) and enriched expression of ETS1, LEF1, GATA1, and TAL1 in M6 and M7 subtypes. A significant correlation between methylation status and expression level was observed for most of these genes in AML patients. Conclusion: Findings from the current study highlight the importance of our cross-species approach in the identification of multiple key candidate genes in AML, which can be further studied to explore their detailed role in leukemia/AML.

The signature based on seven genomic instability-related genes could predict the prognosis of acute myeloid leukemia patients

BACKGROUND

Acute myeloid leukemia (AML) is the most common acute blood malignancy in adults. The complicated and dynamic genomic instability (GI) is the most prominent feature of AML. Our study aimed to explore the prognostic value of GI-related genes in AML patients.

METHODS

The mRNA data and mutation data were downloaded from the TCGA and GEO databases. Differential expression analyses were completed in limma package. GO and KEGG functional enrichment was conducted using clusterProfiler function of R. Univariate Cox and LASSO Cox regression analyses were performed to screen key genes for Risk score model construction. Nomogram was built with rms package.

RESULTS

We identified 114 DEGs between high TMB patients and low TMB AML patients, which were significantly enriched in 429 GO terms and 13 KEGG pathways. Based on the univariate Cox and LASSO Cox regression analyses, seven optimal genes were finally applied for Risk score model construction, including SELE, LGALS1, ITGAX, TMEM200A, SLC25A21, S100A4 and CRIP1. The Risk score could reliably predict the prognosis of AML patients. Age and Risk score were both independent prognostic indicators for AML, and the Nomogram based on them could also reliably predict the OS of AML patients.

CONCLUSIONS

A prognostic signature based on seven GI-related genes and a predictive Nomogram for AML patients are finally successfully constructed.

Controlled variable selection in Weibull mixture cure models for high-dimensional data

Medical breakthroughs in recent years have led to cures for many diseases. The mixture cure model (MCM) is a type of survival model that is often used when a cured fraction exists. Many have sought to identify genomic features associated with a time-to-event outcome which requires variable selection strategies for high-dimensional spaces. Unfortunately, currently few variable selection methods exist for MCMs especially when there are more predictors than samples. This study develops high-dimensional penalized Weibull MCMs, which allow for identification of prognostic factors associated with both cure status and/or survival. We demonstrated how such models may be estimated using two different iterative algorithms. The model-X knockoffs method was combined with these algorithms to control the false discovery rate (FDR) in variable selection. Through extensive simulation studies, our penalized MCMs have been shown to outperform alternative methods on multiple metrics and achieve high statistical power with FDR being controlled. In an acute myeloid leukemia (AML) application with gene expression data, our proposed approach identified 14 genes associated with potential cure and 12 genes with time-to-relapse, which may help inform treatment decisions for AML patients.

Identification of Survival-Related Genes in Acute Myeloid Leukemia (AML) Based on Cytogenetically Normal AML Samples Using Weighted Gene Coexpression Network Analysis

The prognosis of acute myeloid leukemia (AML) remains a challenge. In this study, we applied the weighted gene coexpression network analysis (WGCNA) to find survival-specific genes in AML based on 42 adult CN-AML samples from The Cancer Genome Atlas (TCGA) database. Eighteen hub genes (ABCA13, ANXA3, ARG1, BTNL8, C11orf42, CEACAM1, CEACAM3, CHI3L1, CRISP2, CYP4F3, GPR84, HP, LTF, MMP8, OLR1, PADI2, RGL4, and RILPL1) were found to be related to AML patient survival time. We then compared the hub gene expression levels between AML peripheral blood (PB) samples ( $n=162$ ) and control healthy whole blood samples ( $n=337$ ). Seventeen of the hub genes showed lower expression levels in AML PB samples. The gene expression analysis was also done among AML BM (bone marrow) samples of different stages: diagnosis ( $n=142$ ), posttreatment ( $n=42$ ), and recurrent ( $n=12$ ) stages. The results showed a significant increase of ANXA3, CEACM1, RGL4, RILPL1, and HP in posttreatment samples compared to diagnosis and/or recurrent samples. Transcription factor (TF) prediction of the hub genes suggested LTF as the top hit, overlapping 10 hub genes, while LTF itself is just one of the hub genes. Also, 3671 correlation links were shown between 128 mRNAs and 209 lncRNAs found in survival time-related modules. Generally, we identified candidate mRNA biomarkers based on CN-AML data which can be extensively used in AML prognosis. In addition, we mapped their potential regulatory mechanisms with correlated lncRNAs, providing new insights into potential targets for therapies in AML.

Identification and validation of inferior prognostic genes associated with immune signatures and chemotherapy outcome in acute myeloid leukemia

Acute myeloid leukemia (AML) is a group of heterogeneous hematological malignancies. We identified key genes as ITGAM and lncRNA ITGB2-AS1 through different bioinformatics tools. Furthermore, qPCR was performed to verify the expression level of essential genes in clinical samples. Retrospective research on 179 AML cases was used to investigate the relationship between the expression of ITGAM and the characteristics of AML. The critical gene relationship with immune infiltration in AML was estimated. The clinical validation and prognostic investigation showed that ITGAM, PPBP, and ITGB2-AS1 are highly expressed in AML (P < 0.001) and significantly associated with the overall survival in AML. Moreover, the retrospective research on 179 clinical cases showed that positive expression of ITGAM is substantially related to AML classification (P < 0.001), higher count of white blood cells (P < 0.01), and poor chemotherapy outcome (P < 0.05). Furthermore, based on grouping ITGAM as the high and low expression in TCGA-LAML profile, we found that genes in the highly expressed ITGAM group are mainly involved in immune infiltration and inflammation-related signaling pathways. Finally, we discovered that the expression level of ITGAM and lncRNA ITGB2-AS1 are not just closely related to the immune score and stromal score (P < 0.001) but also significantly positively correlated with various Immune signatures in AML (P < 0.001), indicating the association of these genes with immunosuppression in AML. The prediction of candidate drugs indicated that certain immunosuppressive drugs have potential therapeutic effects for AML. The critical genes could be used as potential biomarkers to evaluate the survival and prognosis of AML.

Clinical significance of CD34+CD117dim/CD34+CD117bri myeloblast-associated gene expression in t(8;21) acute myeloid leukemia

t(8;21)(q22;q22) acute myeloid leukemia (AML) is a highly heterogeneous hematological malignancy with a high relapse rate in China. Two leukemic myeloblast populations (CD34⁺CD117^dim and CD34⁺CD117^bri) were previously identified in t(8;21) AML, and CD34⁺CD117^dim cell proportion was determined as an independent factor for this disease outcome. Here, we examined the impact of CD34⁺CD117^dim/CD34⁺CD117^bri myeloblast-associated gene expression on t(8;21) AML clinical prognosis. In this study, 85 patients with t(8;21) AML were enrolled. The mRNA expression levels of CD34⁺CD117^dim-associated genes (LGALS1, EMP3, and CRIP1) and CD34⁺CD117^bri-associated genes (TRH, PLAC8, and IGLL1) were measured using quantitative reverse transcription PCR. Associations between gene expression and clinical outcomes were determined using Cox regression models. Results showed that patients with high LGALS1, EMP3, or CRIP1 expression had significantly inferior overall survival (OS), whereas those with high TRH or PLAC8 expression showed relatively favorable prognosis. Univariate analysis revealed that CD19, CD34⁺CD117^dim proportion, KIT mutation, minimal residual disease (MRD), and expression levels of LGALS1, EMP3, CRIP1, TRH and PLAC8 were associated with OS. Multivariate analysis indicated that KIT mutation, MRD and CRIP1 and TRH expression levels were independent prognostic variables for OS. Identifying the clinical relevance of CD34⁺CD117^dim/CD34⁺CD117^bri myeloblast-associated gene expression may provide new clinically prognostic markers for t(8;21) AML.

Methylation-independent CRIP1 expression is a potential biomarker affecting prognosis in cytogenetically normal acute myeloid leukemia

Abnormal expression of CRIP1 has been identified in numerous solid tumors. However, CRIP1 expression and its regulation are little known in acute myeloid leukemia (AML). The purpose of this study was to evaluate the expression and regulation of CRIP1 and the clinical implications of CRIP1 aberration in AML. Real-time quantitative PCR was carried out to detect the level of CRIP1 expression in 138 AML patients and 38 controls. CRIP1 methylation was detected by methylation-specific PCR and bisulfite sequencing PCR. Five public available AML datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were further analyzed. The level of CRIP1 expression was up-regulated in AML patients compared with controls (P = 0.045). CRIP1 ^high patients had a significantly lower complete remission (CR) rate than CRIP1 ^low patients (P = 0.020). CRIP1 ^high group had a shorter overall survival (OS) and leukemia-free survival (LFS) than CRIP1 ^low group in cytogenetically normal AML (CN-AML) patients (P = 0.007 and 0.012, respectively). Multivariate analysis further confirmed that high CRIP1 expression was an independent risk factor for LFS in CN-AML patients (P = 0.005). However, we found that CRIP1 expression was not associated with the status of its promoter, which was nearly fully unmethylated both in controls and AML patients. Furthermore, our results were validated using the published GEO datasets and TCGA datasets. Our findings suggest that high CRIP1 expression is independently related with unfavorable prognosis in CN-AML.