Dataset Information

Racial Differences in Four Leukemia Subtypes: Comprehensive Descriptive Epidemiology.

ABSTRACT: Leukemia is a malignant progressive disease and has four major subtypes. Different racial groups differ significantly in multiple aspects. Our goal is to systematically and comprehensively quantify racial differences in leukemia. The SEER database is analyzed, and comprehensive descriptive analysis is provided for the four major subtypes, namely ALL (acute lymphoblastic leukemia), CLL (chronic lymphoblastic leukemia), AML (acute myeloid leukemia), and CML (chronic myeloid leukemia), and for two age groups (?14 and >14) separately. The racial groups studied include NHW (non-Hispanic White), HW (Hispanic White), BL (Black), and API (Asian and Pacific Islander). Univariate and multivariate analyses are conducted to quantify racial differences in patients' characteristics, incidence, and survival. For patients' characteristics, significant racial differences are observed in gender, age at diagnosis, diagnosis era, using radiation for treatment, registry, cancer history, and histology type. For incidence, significant racial differences are observed, and the patterns vary across subtypes, gender, and age groups. For most of the subtypes and gender and age groups, Blacks have the worst five-year survival, and significant racial differences exist. This study provides a comprehensive epidemiologic description of racial differences for the four major leukemia subtypes in the U.S.

SUBMITTER: Zhao Y

PROVIDER: S-EPMC5765036 | biostudies-other | 2018 Jan

REPOSITORIES: biostudies-other

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Racial Differences in Four Leukemia Subtypes: Comprehensive Descriptive Epidemiology.

Zhao Yinjun Y Wang Yu Y Ma Shuangge S

Scientific reports 20180111 1

Leukemia is a malignant progressive disease and has four major subtypes. Different racial groups differ significantly in multiple aspects. Our goal is to systematically and comprehensively quantify racial differences in leukemia. The SEER database is analyzed, and comprehensive descriptive analysis is provided for the four major subtypes, namely ALL (acute lymphoblastic leukemia), CLL (chronic lymphoblastic leukemia), AML (acute myeloid leukemia), and CML (chronic myeloid leukemia), and for two ...[more]

PMID: 29323237

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Project description:Background: Metabolic reprogramming is the core characteristic of tumors during the development of tumors, and cancer cells can rely on metabolic changes to support their rapid growth. Nevertheless, an overall analysis of metabolic markers in acute myeloid leukemia (AML) is absent and urgently needed. Methods: Within this work, genetic expression, mutation data and clinical data of AML were queried from Genotype-Tissue Expression (GTEx) database, The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database. The tumor samples of TCGA were randomly divided into a training group (64 samples) and an internal validation group (64 samples) at one time, and the tumor samples of GEO served as two external validation groups (99 samples, 374 samples). According to the expression levels of survival-associated metabolic genes, we divided all TCGA tumor samples into high, medium and low metabolism groups, and evaluated the immune cell activity in the tumor microenvironment of the three metabolism groups by single-sample gene set enrichment analysis (ssGSEA) algorithm. Finally, we examined the mutations and prognostic effects of each model gene. Results: Four metabolism-related genes were screened and applied to construct a prognostic model for AML, giving excellent results. As for the area under the curve (AUC) value of receiver operating characteristic (ROC) curve, the training group was up to 0.902 (1-year), 0.81 (3-year), and 0.877 (5-year); and the internal and external validation groups also met the expected standards, showing high potency in predicting patient outcome. Univariate and multivariate prognostic analyses indicated that the riskScore obtained from our prognostic model was an independent prognostic factor. ssGSEA analysis revealed the high metabolism group had higher immune activity. Single and multiple gene survival analysis validated that each model gene had significant effects on the overall survival of AML patients. Conclusions: In our study, a high-efficiency prognostic prediction model was built and validated for AML patients. The results showed that metabolism-related genes could become potential prognostic biomarkers for AML.

Dataset Information

Racial Differences in Four Leukemia Subtypes: Comprehensive Descriptive Epidemiology.

Publications

Racial Differences in Four Leukemia Subtypes: Comprehensive Descriptive Epidemiology.

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