Dataset Information

Frequent variations in cancer-related genes may play prognostic role in treatment of patients with chronic myeloid leukemia.

ABSTRACT:

Background

Genome variability of host genome and cancer cells play critical role in diversity of response to existing therapies and overall success in treating oncological diseases. In chronic myeloid leukemia targeted therapy with tyrosine kinase inhibitors demonstrates high efficacy in most of the patients. However about 15 % of patients demonstrate primary resistance to standard therapy. Whole exome sequencing is a good tool for unbiased search of genetic variations important for prognosis of survival and therapy efficacy in many cancers. We apply this approach to CML patients with optimal response and failure of tyrosine kinase therapy.

Results

We analyzed exome variations between optimal responders and failures and found 7 variants in cancer-related genes with different genotypes in two groups of patients. Five of them were found in optimal responders: rs11579366, rs1990236, rs176037, rs10653661, rs3803264 and two in failures: rs3099950, rs9471966. These variants were found in genes associated with cancers (ANKRD35, DNAH9, MAGEC1, TOX3) or participating in cancer-related signaling pathways (THSD1, MORN2, PTCRA).

Conclusion

We found gene variants which may become early predictors of the therapy outcome and allow development of new early prognostic tests for estimation of therapy efficacy in CML patients. Normal genetic variation may influence therapy efficacy during targeted treatment of cancers.

SUBMITTER: Lavrov AV

PROVIDER: S-EPMC4895599 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Frequent variations in cancer-related genes may play prognostic role in treatment of patients with chronic myeloid leukemia.

Lavrov Alexander V AV Chelysheva Ekaterina Y EY Smirnikhina Svetlana A SA Shukhov Oleg A OA Turkina Anna G AG Adilgereeva Elmira P EP Kutsev Sergey I SI

BMC genetics 20160127

<h4>Background</h4>Genome variability of host genome and cancer cells play critical role in diversity of response to existing therapies and overall success in treating oncological diseases. In chronic myeloid leukemia targeted therapy with tyrosine kinase inhibitors demonstrates high efficacy in most of the patients. However about 15 % of patients demonstrate primary resistance to standard therapy. Whole exome sequencing is a good tool for unbiased search of genetic variations important for prog ...[more]

PMID: 26822197

Similar Datasets

Project description:BackgroundChemotactic cytokines play a crucial role in the development of acute myeloid leukemia (AML). Thus, investigating the mechanisms of chemotactic cytokine-related genes (CCRGs) in AML is of paramount importance.MethodsUsing the TCGA-AML, GSE114868, and GSE12417 datasets, differential expression analysis identified differentially expressed CCRGs (DE-CCRGs). These genes were screened by overlapping differentially expressed genes (DEGs) between AML and control groups with CCRGs. Subsequently, functional enrichment analysis and the construction of a protein-protein interaction (PPI) network were conducted to explore the functions of the DE-CCRGs. Univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses identified relevant prognostic genes and developed a prognostic model. Survival analysis of the prognostic gene was performed, followed by functional similarity analysis, immune analysis, enrichment analysis, and drug prediction analysis.ResultsDifferential expression analysis revealed 6,743 DEGs, of which 29 DE-CCRGs were selected for this study. Functional enrichment analysis indicated that DE-CCRGs were primarily involved in chemotactic cytokine-related functions and pathways. Six prognostic genes (CXCR3, CXCR2, CXCR6, CCL20, CCL4, and CCR2) were identified and incorporated into the risk model. The model's performance was validated using the GSE12417 dataset. Survival analysis showed significant differences in AML overall survival (OS) between prognostic gene high and low expression groups, indicating that prognostic gene might be significantly associated with patient survival. Additionally, nine different immune cells were identified between the two risk groups. Correlation analysis revealed that CCR2 had the most significant positive correlation with monocytes and the most significant negative correlation with resting mast cells. The tumor immune dysfunction and exclusion score was lower in the high-risk group.ConclusionCXCR3, CXCR2, CXCR6, CCL20, CCL4, and CCR2 were identified as prognostic genes correlated to AML and the tumor immune microenvironment. These findings offerred novel insights into the prevention and treatment of AML.

Project description:IntroductionAcute myeloid leukemia(AML) is a diverse malignancy with a prognosis that varies, being especially unfavorable in older patients and those with high-risk characteristics. Metabolic reprogramming has become a significant factor in AML development , presenting new opportunities for prognostic assessment and therapeutic intervention.MethodsMetabolism-related differentially expressed genes (mDEGs) were identified by integrating KEGG metabolic gene lists with AML gene expression data from GSE63270. Using TCGA data, we performed consensus clustering and survival analysis to investigate the prognostic significance of mDEGs. A metabolic risk model was constructed using LASSO Cox reg ression and enhanced by a nomogram incorporated clinical characteristics. The model was validated through receiver operating characteristic (ROC) curves and survival statistics. Gene network analysis was conducted to identify critical prognostic factors. The tumor immune microenvironment was evaluated using CIBERSORT and ESTIMATE algorithms, followed by correlation analysis between immune checkpoint gene expression and risk scores. Drug sensitivity predictions and in vitro assays were performed to explore the effects of mDEGs on cell proliferation and chemoresistance.ResultsAn 11-gene metabolic prognostic model was established and validated. High-risk patients had worse overall survival in both training and validation cohorts (p < 0.05). The risk score was an independent prognostic factor. High-risk patients showed increased immune cell infiltration and potential response to checkpoint inhibitors but decreased drug sensitivity. The model correlated with sensitivity to drugs such as venetoclax. Carbonic anhydrase 13 (CA13) was identified as a key gene related to prognosis and doxorubicin resistance. Knocking down CA13 reduced proliferation and increased cell death with doxorubicin treatment.ConclusionA novel metabolic gene signature was developed to stratify risk and predict prognosis in AML, serving as an independent prognostic factor. CA13 was identified as a potential therapeutic target. This study provides new insights into the prognostic and therapeutic implications of metabolic genes in AML.

Project description:A previous study has demonstrated a significant decrease in the TCR? gene expression level in chronic myeloid leukemia (CML); thus, we further investigated the expression of TCR?-regulating factors, the distribution of the TCR? 3' untranslated region (3'-UTR) splice variants, and the expression level and correlation of the alternative splicing factor/splicing factor 2 (ASF/SF-2), Fc?RI? and ZAP-70 genes. TCR? 3'-UTR splice variants were identified in peripheral blood mononuclear cells (PBMCs) from 14 healthy individuals, 40 patients with CML and 22 patients with CML in complete remission (CML-CR) by RT-PCR. The expression level of the TCR?, Fc?RI?, ASF/SF-2 and ZAP-70 genes was analyzed by real-time quantitative PCR. While the expression of TCR? gene in the CML group was significantly lower than that in the healthy individual and CML-CR groups, a significantly higher expression of the FceRI? and ASF/SF-2 genes was found in the CML group. Two types of splicing forms were detected in all of the healthy individual CML-CR cases: wild type (WT) TCR? 3'-UTR and alternatively splieced (AS) TCR? 3'-UTR which have been alternatively splieced in the WT TCR? 3'-UTR . However, 35% of the CML cases contained only the wild type TCR? 3'-UTR isoform. Based on the TCR? 3'-UTR isoform expression characteristic, we divided the patients with CML into two subgroups: the WT+AS- CML group, containing patients that express only the wild type TCR? 3'-UTR, and the WT+AS+ CML group, which contained patients that expressed two TCR? 3'-UTR isoforms. A significantly different ASF/SF-2 and Fc?RI? gene expression pattern was found between the WT+AS- and WT+AS+CML groups. We concluded that defective TCR? expression may be characterized in the WT+AS-and WT+AS+CML subgroups by the different gene expression pattern. The overexpression of ASF/SF2, which alternatively splices the TCR? 3'-UTR, is thought to participate in feedback regulation. The characteristics of TCR? 3'-UTR alternative splicing may be a novel immunological marker for the evaluation of the CML immune status.

Project description:BackgroundAcute myeloid leukemia (AML) is an aggressive hematological neoplasm. Little improvement in survival rates has been achieved over the past few decades. Necroptosis has relationship with certain types of malignancies outcomes. Here, we evaluated the diagnostic ability, prognostic capacity of necroptosis-related genes (NRGs) and the effect of their copy number variations (CNVs) in AML.MethodsNecroptosis-related differentially expressed genes (NRDEGs) were identified after intersecting differentially expressed genes (DEGs) from the Gene Expression Omnibus(GEO) database with NRGs from GeneCards, the Molecular Signatures Database (MSigDB) and literatures. Machine learning was applied to obtain hub-NRDEGs. The expression levels of the hub-NRDEGs were validated in vitro. The mRNA-miRNA and mRNA-TF interaction networks with the hub-NRDEGs were screened using Cytoscape@. Single-sample gene set enrichment analysis (ssGSEA) was utilized to calculate correlations between the hub-NRDEGs and immune cells. CNV analysis of the hub-NRDEGs was carried out on the TCGA-LAML datasets from the TCGA database. Kaplan-Meier (K-M) survival analyses were utilized to evaluate the prognostic values along with Cox model.ResultsSix hub-NRDEGs (SLC25A5, PARP1, CTSS, ZNF217, NFKB1, and PYGL) were obtained and their expression changes derived from CNVs in AML were visualized. In total, 65 mRNA-miRNA and 80 mRNA-TF interaction networks with hub-NRDEGs were screened. The ssGSEA result showed the expression of RAPR1 was inversely related to CD56dim natural killer cells and the expression of CTSS was positive related to Myeloid-derived suppressor cells (MDSCs) in AML. The K-M results demonstrated that ZNF217 had significant difference in the duration of survival in AML patients. Cox regression models revealed that the hub-NRDEGs had better predictive power at year-1 and year-5.ConclusionThese screened NRDEGs can be exploited as clinical prognostic predictions in AML patients, as well as potential biomarkers for diagnosis and therapeutic targeting.

Dataset Information

Frequent variations in cancer-related genes may play prognostic role in treatment of patients with chronic myeloid leukemia.

Background

Results

Conclusion

Publications

Frequent variations in cancer-related genes may play prognostic role in treatment of patients with chronic myeloid leukemia.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets