Dataset Information

Comprehensive Analysis of CRIP1 Expression in Acute Myeloid Leukemia.

ABSTRACT: Acute myeloid leukemia (AML) is a highly heterogeneous hematological malignancy that imposes great challenges in terms of drug resistance and relapse. Previous studies revealed heterogeneous leukemia cells and their relevant gene markers, such as CRIP1 as clinically prognostic in t (8;21) AML patients. However, the expression and role of CRIP1 in AML are poorly understood. We used the single-cell RNA sequencing and gene expression data from t (8;21) AML patients to analyze the immune and regulation networks of CRIP1. Two independent cohorts from GSE37642 and The Cancer Genome Atlas (TCGA) datasets were employed as validation cohorts. In addition, the methylation data from TCGA were used to analyze the methylation effect of the CRIP1 expression. Gene expression profile from t (8;21) AML patients showed that the CRIP1-high group exhibited an enrichment of immune-related pathways, including tumor necrosis factor (TNF)α signaling via nuclear factor kappa B (NFκB) pathways. Further studies using CIBERSORT showed that the CRIP1-high group had a significantly higher infiltration of exhausted CD8 T cells and activated mast cells. The CRIP1 expression was validated in the GSE37642-GPL96, GSE37642-GPL570, and TCGA datasets. In addition, with the methylation data, four CpG probes of CRIP1 (cg07065217, cg04411625, cg25682097, and 11763800) were identified as negatively associated with the CRIP1 gene expression in AML patients. Our data provide a comprehensive overview of the regulation of CRIP1 expression in AML patients. The evaluation of the TNFα-NFκB signaling pathway as well as the immune heterogeneity might provide new insights for exploring improvements in AML treatment.

SUBMITTER: Gao Y

PROVIDER: S-EPMC9354089 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Comprehensive Analysis of CRIP1 Expression in Acute Myeloid Leukemia.

Gao Yan Y Li Jin-Yuan JY Mao Jia-Ying JY Zhou Jia-Fan JF Jiang Lu L Li Xue-Ping XP

Frontiers in genetics 20220722

Acute myeloid leukemia (AML) is a highly heterogeneous hematological malignancy that imposes great challenges in terms of drug resistance and relapse. Previous studies revealed heterogeneous leukemia cells and their relevant gene markers, such as CRIP1 as clinically prognostic in t (8;21) AML patients. However, the expression and role of CRIP1 in AML are poorly understood. We used the single-cell RNA sequencing and gene expression data from t (8;21) AML patients to analyze the immu ...[more]

PMID: 35938037

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Project description:Background: Tyrosyl phosphorylation is carried out by a group of enzymes known as non-receptor protein tyrosine phosphatases (PTPNs). In the current investigation, it is hoped to shed light on the relationships between the expression patterns of PTPN family members and the prognosis of acute myeloid leukemia (AML). Methods: PTPN expression was examined using GEPIA and GEO databases. To investigate the connection between PTPN expression and survival in AML patients, we downloaded data from the Broad TCGA Firehose and Clinical Proteomic Tumor Analysis (CPTAC) of the Cancer Genome Atlas (TCGA). We used quantitative real-time PCR (qRT-PCR) to confirm that essential genes were performed in clinical samples and cell lines. We then used western blot to verify that the genes expressed in the above databases were positive in normal tissues, AML patient samples, and AML cell lines. Next, we investigated associations between genome-wide expression profiles and PTPN6 expression using the GEO datasets. We investigated the interactive exploration of multidimensional cancer genomics using the cBioPortal datasets. Using the DAVID database, a study of gene ontology enrichment was performed. The protein-protein interaction (PPI) network was created using the STRING portal, and the gene-gene interaction network was performed using GeneMANIA. Results: Data from GEO and GEPIA revealed that most PTPN family members were linked to AML. Patients with leukemia have elevated levels of several PTPN members. All of the AML patients' poor overall survival (OS, p < .05) was significantly linked with higher expression of PTPN1, PTPN6, and PTPN7. Additionally, clinical samples showed that the expression of PTPN 6, PTPN 7, PTPN 13, and PTPN 14 was higher than normal in AML patients (p = .0116, p = .0034, p = .0092, and p = .0057, respectively) and AML cell lines (p = .0004, p = .0035, p = .0357, and p = .0177, respectively). Western blotting results showed that the expression of PTPN6 in AML samples and AML cell lines was significantly higher than that in normal control samples. Conclusion: Differentially expressed PTPN family members were found in AML. The prognosis of patients and PTPN gene expression were shown to be correlated. PTPN6 is one of these members and may be used as an AML diagnostic and prognostic marker.

Project description:The V-domain Ig suppressor of T-cell activation (VISTA) has been recognized as a critical negative regulator of antitumor immune response and is gaining growing interest as a potential pharmacological target in immunotherapy. This molecule is highly expressed in hematopoietic stem cells and myeloid compartment, and it has been found upmodulated in acute myeloid leukemia (AML). However, VISTA-associated immune features are relatively unexplored in myeloid malignancies. Herein, we aimed to explore whether this immune checkpoint regulator could play a role in the generation of an immune escape environment in AML patients. We characterized VISTA mRNA expression levels in leukemia cell lines and in large publicly available cohorts of specimens from bone marrow of healthy individuals and AML patients at diagnosis by deploying bulk and single-cell RNA sequencing. We also defined the correlations with leukemia-associated burden using results of whole-exome sequencing of AML samples at disease onset. We showed that VISTA expression linearly increased across the myeloid differentiation tree in normal hematopoiesis. Accordingly, its transcript was highly enriched in AML cell lines as well as in AML patients at diagnosis presenting with myelomonocytic and monocytic differentiation. A strong correlation was seen with NPM1 mutations regardless of the presence of FLT3 lesions. Furthermore, VISTA expression levels at baseline correlated with disease recurrence in patients with normal karyotype and NPM1 mutations, a subgroup traditionally considered as favorable according to current diagnostic schemes. Indeed, when compared to patients with long-term remission (>5 years after standard chemotherapy regimens), cases relapsing within 2 years from diagnosis had increased VISTA expression in both leukemia and T cells. Our results suggest a rationale for developing VISTA-targeted therapeutic strategies to treat molecularly defined subgroups of AML patients to prevent disease recurrence and treatment resistance.

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Project description:Gene expression is a combinatorial function of genetic/epigenetic factors such as copy number variation (CNV), DNA methylation (DM), transcription factors (TF) occupancy, and microRNA (miRNA) post-transcriptional regulation. At the maturity of microarray/sequencing technologies, large amounts of data measuring the genome-wide signals of those factors became available from Encyclopedia of DNA Elements (ENCODE) and The Cancer Genome Atlas (TCGA). However, there is a lack of an integrative model to take full advantage of these rich yet heterogeneous data. To this end, we developed RACER (Regression Analysis of Combined Expression Regulation), which fits the mRNA expression as response using as explanatory variables, the TF data from ENCODE, and CNV, DM, miRNA expression signals from TCGA. Briefly, RACER first infers the sample-specific regulatory activities by TFs and miRNAs, which are then used as inputs to infer specific TF/miRNA-gene interactions. Such a two-stage regression framework circumvents a common difficulty in integrating ENCODE data measured in generic cell-line with the sample-specific TCGA measurements. As a case study, we integrated Acute Myeloid Leukemia (AML) data from TCGA and the related TF binding data measured in K562 from ENCODE. As a proof-of-concept, we first verified our model formalism by 10-fold cross-validation on predicting gene expression. We next evaluated RACER on recovering known regulatory interactions, and demonstrated its superior statistical power over existing methods in detecting known miRNA/TF targets. Additionally, we developed a feature selection procedure, which identified 18 regulators, whose activities clustered consistently with cytogenetic risk groups. One of the selected regulators is miR-548p, whose inferred targets were significantly enriched for leukemia-related pathway, implicating its novel role in AML pathogenesis. Moreover, survival analysis using the inferred activities identified C-Fos as a potential AML prognostic marker. Together, we provided a novel framework that successfully integrated the TCGA and ENCODE data in revealing AML-specific regulatory program at global level.

Dataset Information

Comprehensive Analysis of CRIP1 Expression in Acute Myeloid Leukemia.

Publications

Comprehensive Analysis of <i>CRIP1</i> Expression in Acute Myeloid Leukemia.

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