Rare t(X;14)(q28;q32) translocation reveals link between MTCP1 and chronic lymphocytic leukemia

Identification of t(X;1)(q28;q21) generating a novel GATAD2B::MTCP1 gene fusion in CMML and its persistence during progression to AML

OBJECTIVE

Hematological malignancies often involve chromosomal translocations and fusion genes that drive disease progression. While MTCP1 is well-known in T-cell prolymphocytic leukemia (T-PLL), its role in myeloid neoplasms is less understood. This report presents the first identification of the t(X;1)(q28;q21) translocation leading to the GATAD2B::MTCP1 fusion in acute myeloid leukemia (AML) transformed from chronic myelomonocytic leukemia (CMML).

METHODS

The karyotypes were described according to the International System for Human Cytogenetic Nomenclature 2009. We performed targeted next-generation sequencing (NGS) on a panel of 172 genes commonly mutated in hematological malignancies (Supplemental Table 1), using an Illumina platform. RNA sequencing was conducted on total RNA extracted from bone marrow, also using the Illumina platform. The GATAD2B::MTCP1 fusion gene was confirmed by reverse transcription-polymerase chain reaction (RT-PCR) and Sanger sequencing, with specific primers for the fusion transcript (GATAD2B-F: CCTCTTTTTTTCGACGCC; MTCP1-R: ACTGAGCACAACACTTACGC).

RESULTS

The GATAD2B::MTCP1 fusion results from a breakpoint on 1q21 within GATAD2B exon 1 and Xq28 within MTCP1 exon 2. The patient with the GATAD2B::MTCP1 fusion exhibited disease progression from CMML to AML. Despite achieving initial remission with venetoclax-based therapy and allo-HSCT, the patient relapsed and died.

CONCLUSIONS

We propose that the GATAD2B::MTCP1 fusion upregulates MTCP1 expression rather than generating a fusion protein, thereby contributing to transformation and relapse in AML. Further investigations are needed to elucidate the precise role of this fusion event in myeloid malignancies.

Optical genome mapping with genome sequencing identifies subtelomeric Xq28 deletion and inserted 7p22.3 duplication in a male with multisystem developmental disorder

We report a 17-year-old male with supravalvular stenosis, initial failure to thrive and delayed early development, short stature, acromelia, dysmorphic facial features, hypertelorism, macrocephaly, syringomyelia, hypertension, and anxiety disorder. Fluorescent in situ hybridization (FISH), chromosomal microarray analysis (CMA), and exome sequencing (ES) were nondiagnostic. Combined optical genome mapping (OGM) and genome sequencing (GS) showed a complex rearrangement including an X chromosome with a 22.5 kb deletion in band Xq28 replaced by a 61.4 kb insertion of duplicated chromosome 7p22.3 material. The deletion removes the distal 3' untranslated region (UTR) of FUNDC2, the entire CMC4 and MTCP1, and the first five exons of BRCC3. Transcriptome analysis revealed absent expression of CMC4 and MTCP1 and BRCC3 with normal transcript level of FUNDC2. The inserted duplication includes only one known gene: UNCX. Similar overlapping Xq28 deletions have been reported to be associated with Moyamoya disease (MMD), short stature, hypergonadotropic hypogonadism (HH), and facial dysmorphism. Although he has short stature, our patient does not have signs of Moyamoya arteriopathy or hypogonadism. The structurally abnormal X chromosome was present in his mother, but not in his unaffected brother, maternal uncle, or maternal grandparents. We propose that the combination of his absent Xq28 and duplicated 7p22.3 genomic material is responsible for his phenotype. This case highlights the potential of combined OGM and GS for detecting complex structural variants compared with standard of care genetic testing such as CMA and ES.

Perfluorooctanesulfonic acid (PFOS) induced cancer related DNA methylation alterations in human breast cells: A whole genome methylome study

DNA methylation plays a pivotal role in cancer. The ubiquitous contaminant perfluorooctanesulfonic acid (PFOS) has been epidemiologically associated with breast cancer, and can induce proliferation and malignant transformation of normal human breast epithelial cells (MCF-10A), but the information about its effect on DNA methylation is sparse. The aim of this study was to characterize the whole-genome methylome effects of PFOS in our breast cell model and compare the findings with previously demonstrated DNA methylation alterations in breast tumor tissues. The DNA methylation profile was assessed at single CpG resolution in MCF-10A cells treated with 1 μM PFOS for 72 h by using Enzymatic Methyl sequencing (EM-seq). We found 12,591 differentially methylated CpG-sites and 13,360 differentially methylated 100 bp tiles in the PFOS exposed breast cells. These differentially methylated regions (DMRs) overlapped with 2406 genes of which 494 were long non-coding RNA and 1841 protein coding genes. We identified 339 affected genes that have been shown to display altered DNA methylation in breast cancer tissue and several other genes related to cancer development. This includes hypermethylation of GACAT3, DELEC1, CASC2, LCIIAR, MUC16, SYNE1 and hypomethylation of TTN and KMT2C. DMRs were also found in estrogen receptor genes (ESR1, ESR2, ESRRG, ESRRB, GREB1) and estrogen responsive genes (GPER1, EEIG1, RERG). The gene ontology analysis revealed pathways related to cancer phenotypes such as cell adhesion and growth. These findings improve the understanding of PFOS's potential role in breast cancer and illustrate the value of whole-genome methylome analysis in uncovering mechanisms of chemical effects, identifying biomarker candidates, and strengthening epidemiological associations, potentially impacting risk assessment.

Identification and validation of three potential biomarkers and immune microenvironment for in severe asthma in microarray and single-cell datasets

Objective: The aim of this study was to identify genetic biomarkers and cellular communications associated with severe asthma in microarray data sets and single cell data sets. The potential gene expression levels were verified in a mouse model of asthma.Methods: We identified differentially expressed genes from the microarray datasets (GSE130499 and GSE63142) of severe asthma, and then constructed models to screen the most relevant biomarkers to severe asthma by machine learning algorithms (LASSO and SVM-RFE), with further validation of the results by GSE43696. Single-cell datasets (GSE193816 and GSE227744) were identified for potential biomarker-specific expression and intercellular communication. Finally, The expression levels of potential biomarkers were verified with a mouse model of asthma.Results: The 73 genes were differentially expressed between severe asthma and normal control. LASSO and SVM-RFE recognized three genes BCL3, DDIT4 and S100A14 as biomarkers of severe asthma and had good diagnostic effect. Among them, BCL3 transcript level was down-regulated in severe asthma, while S100A14 and DDIT4 transcript levels were up-regulated. The transcript levels of the three genes were confirmed in the mouse model. Infiltration of neutrophils and mast cells were found to be increased in severe asthma and may be associated with bronchial epithelial cells through BMP and NRG signalingConclusions: We identified three differentially expressed genes (BCL3, DDIT4 and S100A14) of diagnostic significance that may be involved in the development of severe asthma and these gene expressions could be serviced as biomarker of severe asthma and investigating the function roles could bring new insights into the underlying mechanisms.

A prognostic 15-gene model based on differentially expressed genes among metabolic subtypes in diffuse large B-cell lymphoma

The outcomes of patients with diffuse large B-cell lymphoma (DLBCL) vary widely, and about 40% of them could not be cured by the standard first-line treatment, R-CHOP, which could be due to the high heterogeneity of DLBCL. Here, we aim to construct a prognostic model based on the genetic signature of metabolic heterogeneity of DLBCL to explore therapeutic strategies for DLBCL patients. Clinical and transcriptomic data of one training and four validation cohorts of DLBCL were obtained from the GEO database. Metabolic subtypes were identified by PAM clustering of 1,916 metabolic genes in the 7 major metabolic pathways in the training cohort. DEGs among the metabolic clusters were then analyzed. In total, 108 prognosis-related DEGs were identified. Through univariable Cox and LASSO regression analyses, 15 DEGs were used to construct a risk score model. The overall survival (OS) and progression-free survival (PFS) of patients with high risk were significantly worse than those with low risk (OS: HR 2.86, 95%CI 2.04-4.01, p < 0.001; PFS: HR 2.42, 95% CI 1.77-3.31, p < 0.001). This model was also associated with OS in the four independent validation datasets (GSE10846: HR 1.65, p = 0.002; GSE53786: HR 2.05, p = 0.02; GSE87371: HR 1.85, p = 0.027; GSE23051: HR 6.16, p = 0.007) and PFS in the two validation datasets (GSE87371: HR 1.67, p = 0.033; GSE23051: HR 2.74, p = 0.049). Multivariable Cox analysis showed that in all datasets, the risk model could predict OS independent of clinical prognosis factors (p < 0.05). Compared with the high-risk group, patients in the low-risk group predictively respond to R-CHOP (p = 0.0042), PI3K inhibitor (p < 0.05), and proteasome inhibitor (p < 0.05). Therefore, in this study, we developed a signature model of 15 DEGs among 3 metabolic subtypes, which could predict survival and drug sensitivity in DLBCL patients.

VIP152 is a selective CDK9 inhibitor with pre-clinical in vitro and in vivo efficacy in chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is effectively treated with targeted therapies including Bruton tyrosine kinase inhibitors and BCL2 antagonists. When these become ineffective, treatment options are limited. Positive transcription elongation factor complex (P-TEFb), a heterodimeric protein complex composed of cyclin dependent kinase 9 (CDK9) and cyclin T1, functions to regulate short half-life transcripts by phosphorylation of RNA Polymerase II (POLII). These transcripts are frequently dysregulated in hematologic malignancies; however, therapies targeting inhibition of P-TEFb have not yet achieved approval for cancer treatment. VIP152 kinome profiling revealed CDK9 as the main enzyme inhibited at 100 nM, with over a 10-fold increase in potency compared with other inhibitors currently in development for this target. VIP152 induced cell death in CLL cell lines and primary patient samples. Transcriptome analysis revealed inhibition of RNA degradation through the AU-Rich Element (ARE) dysregulation. Mechanistically, VIP152 inhibits the assembly of P-TEFb onto the transcription machinery and disturbs binding partners. Finally, immune competent mice engrafted with CLL-like cells of Eµ-MTCP1 over-expressing mice and treated with VIP152 demonstrated reduced disease burden and improvement in overall survival compared to vehicle-treated mice. These data suggest that VIP152 is a highly selective inhibitor of CDK9 that represents an attractive new therapy for CLL.