Identification of a novel MEF2C::SS18L1 fusion in childhood acute B-lymphoblastic leukemia.

PURPOSE: Leukemia-associated fusion genes are closely related to the occurrence, development, diagnosis, and treatment of leukemia. DNA microarrays and second-generation sequencing have discovered multiple B-ALL fusion genes. We identified a novel MEF2C::SS18L1 fusion gene in a child diagnosed with B-ALL. This study investigates the oncogenicity and prognosis of this fusion gene in B-ALL. METHODS: A child with B-ALL who has a MEF2C::SS18L1 fusion is reported as a newly discovered case. Compared the breakpoints, structural domains, clinical phenotypes, and differential expression genes of MEF2C::SS18L1 and MEF2D::SS18.Using "ONCOFUSE" software, the carcinogenicity of MEF2C::SS18L1 is predicted. Using whole transcriptome sequencing, we analyze the breakpoints and the secondary structure of the fusion protein. Further, we compared the structures, differentially expressed genes, and clinical phenotypes of MEF2D and MEF2C fusion genes by DESeq, GO functional enrichment, and flow cytometry immunophenotyping analysis. RESULTS: Whole transcriptome sequencing identified a MEF2C::SS18L1 fusion transcript in a 3-year-old child with B-ALL. The MADS box, MEF structural domain, HJURP_C structural domain, and TAD I structural domain of MEF2C, and the QPGY structural domain of SS18L1, make up the fusion protein. "Oncofuse" found a 0.99 Bayesian probability that the fusion gene drives cancer. The breakpoint positions, fusion protein secondary structures, differentially expressed genes, and clinical characteristics of this patient were identical to those with MEF2D::SS18 fusion gene. CONCLUSION: We identified a novel MEF2C::SS18L1 fusion gene in childhood ALL, which shares similar structural and clinical characteristics with MEF2D::SS18. Further studies with more samples should be conducted in future.

KIF11 serves as a cell cycle mediator in childhood acute lymphoblastic leukemia.

OBJECTIVE: To identify key gene in childhood acute lymphoblastic leukemia (ALL) through weighted gene co-expression network analysis (WGCNA), and their enriched biological functions and signaling pathways. METHODS: Array data of the GSE73578 dataset, involving 46 childhood ALL samples, were acquired from the Gene Expression Omnibus (GEO) database. Hub modules associated with childhood ALL were screened out by WGCNA. Enriched biological functions and signaling pathways were then identified by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Hub genes were selected by overlapping those between down-regulated genes in GSE73578, GSE4698 and the hub module. Guilt by association (GBA) was adopted to verify the function of the identified KIF11 gene and to predict its target genes. Regulatory effects of KIF11 on the proliferation and cell cycle progression of ALL in vitro were determined by cytological experiments. RESULTS: WGCNA showed that the yellow module was the most relevant to childhood ALL treatment, containing 698 genes that were enriched in cell division, mitotic nuclear division, DNA replication and DNA repair, cell cycle, DNA replication and the P53 signaling pathway. The KIF11 gene was screened out and predicted as a cell cycle mediator in childhood ALL. Knockdown of KIF11 in ALL cells inhibited cell proliferation and arrested cell cycle progression in G2/M phase. CONCLUSIONS: The KIF11 gene is critical in the treatment process of childhood ALL, which is a promising therapeutic target for childhood ALL.

Construction of a novel anoikis-related prognostic model and analysis of its correlation with infiltration of immune cells in neuroblastoma.

Background: Anoikis resistance (AR) plays an important role in the process of metastasis, which is an important factor affecting the risk stage of neuroblastoma (NB). This study aims to construct an anoikis-related prognostic model and analyze the characteristics of hub genes, important pathways and tumor microenvironment of anoikis-related subtypes of NB, so as to provide help for the clinical diagnosis, treatment and research of NB. Methods: We combined transcriptome data of GSE49710 and E-MTAB-8248, screened anoikis-related genes (Args) closely related to the prognosis of NB by univariate cox regression analysis, and divided the samples into anoikis-related subtypes by consistent cluster analysis. WGCNA was used to screen hub genes, GSVA and GSEA were used to analyze the differentially enriched pathways between anoikis-related subtypes. We analyzed the infiltration levels of immune cells between different groups by SsGSEA and CIBERSORT. Lasso and multivariate regression analyses were used to construct a prognostic model. Finally, we analyzed drug sensitivity through the GDSC database. Results: 721 cases and 283 Args were included in this study. All samples were grouped into two subtypes with different prognoses. The analyses of WGCNA, GSVA and GSEA suggested the existence of differentially expressed hub genes and important pathways in the two subtypes. We further constructed an anoikis-related prognostic model, in which 15 Args participated. This model had more advantages in evaluating the prognoses of NB than other commonly used clinical indicators. The infiltration levels of 9 immune cells were significantly different between different risk groups, and 13 Args involved in the model construction were correlated with the infiltration levels of immune cells. There was a relationship between the infiltration levels of 6 immune cells and riskscores. Finally, we screened 15 drugs with more obvious effects on NB in high-risk group. Conclusion: There are two anoikis-related subtypes with different prognoses in the population of NB. The anoikis-related prognostic model constructed in this study can accurately predict the prognoses of children with NB, and has a good guiding significance for clinical diagnosis, treatment and research of NB.

Identification of hub genes and their correlation with infiltration of immune cells in MYCN positive neuroblastoma based on WGCNA and LASSO algorithm.

Background: The prognosis of MYCN positive NB is poor, and there is no targeted drug for N-myc at present. This study aims to screen out hub genes closely related to MYCN, analyze the relationship between hub genes and NB microenvironment, and provide basis for molecular targeted therapy of MYCN positive NB. Methods: We combined the microarray data of GSE45547 (n=649) and GSE49710 (n=498), screened the DEGs between MYCN positive (n=185) and MYCN negative NB (n=951), performed WGCNA, Lasso regression and Roc analyses on the merged matrix, and obtained the hub genes related to MYCN in the training group. We performed ssGSEA on the experimental group to calculate the infiltration level of 28 kinds of immune cells in each sample, compared the differences of immune cell infiltration between MYCN positive and MYCN negative group. The influences of hub genes on the distribution of each immune cell were also analyzed by ssGSEA. The expression differences of the three hub genes were verified in the E-MTAB-8248 cohort (n=223), and the correlation between hub genes and prognosis of NB was calculated by Kaplan-Meier method in GSE62564 (n=498) and the validation group. We also verified the expression differences of hub genes by qRT-PCR in SK-N-BE(2), SKNDZ, Kelly and SH-SY5Y cell lines. Results: Here were 880 DEGs including 420 upregulated and 460 downregulated genes in MYCN positive NB in the training group. Overlap of the DEGs and WGCNA networks identified four shared genes, namely, ZNF695, CHEK1, C15ORF42 and EXO1, as candidate hub genes in MYCN positive NB. Three core genes, ZNF695, CHEK1 and C15ORF42, were finally identified by Lasso regression and Roc analyses. ZNF695, CHEK1 and C15ORF42 were highly expressed in MYCN positive NB tissues and cell lines. These three genes were closely related to the prognosis of children with NB. Except that Activated CD4 T cell and Type2 T helper cell increased, the infiltration levels of the other 26 cells decreased significantly in MYCN positive NB tissues. The infiltration levels of Type2 T helper cell and Activated CD4 T cell were also significantly positively correlated with the expression levels of the three hub genes. Conclusion: ZNF695, CHEK1 and C15ORF42 are highly expressed in MYCN positive NB, and their expression levels are negatively correlated with the prognosis of children with NB. The infiltration levels of Activated CD4 T cell and Type2 T helper cell increased in the microenvironment of MYCN positive NB and were significantly positively correlated with the expression levels of the three hub genes. The results of this study provide that ZNF695, CHEK1 and C15ORF42 may be potential prognostic markers and immunotherapy targets for MYCN positive NB.

Case Report: A Novel CXCR4 Mutation in a Chinese Child With Kawasaki Disease Causing WHIM Syndrome.

WHIM syndrome, an extremely rare congenital disease with combined immunodeficiency, is mainly caused by heterozygous gain-of-function mutation in the CXCR4 gene. There have been no previous case reports of WHIM syndrome with Kawasaki disease. We herein report a case of a boy who developed Kawasaki disease at the age of 1 year. After treatment, the number of neutrophils in his peripheral blood decreased continuously. His medical history revealed that he had been suffering from leukopenia, neutropenia and low immunoglobulin since birth, and his neutrophils could return to the normal level in the presence of infection or inflammation. Clinical targeted gene sequencing of 91 genes associated with granulocyte-related disease revealed that the patient had a novel heterozygous NM_003467; c.1032_1033delTG;p.(E345Vfs*12) variant in exon 2 of CXCR4 gene. Family verification analysis by Sanger sequencing showed that his father also had heterozygous variation at this site, while other family members did not. The computer prediction software indicated that the variation had a high pathogenicity. The computational structure analysis of the mutant revealed significant structural and functional changes in the CXCR4 protein. It should be noted that when unexplained persistent neutropenia with low immunoglobulin occurs after birth, especially when there is a family history of neutropenia, immunodeficiency should be investigated with genetic testing.