Identification and characterization of ectopic chromosomal amplifications in acute myeloid leukemia cell limes using high-throughput chromosome conformation capture screening.

Tetsuko Kobayashi; Satsuki Matsushima; Hiroaki Ohnishi

doi:10.1016/j.leukres.2026.108304

PubMed · 42721719

Identification and characterization of ectopic chromosomal amplifications in acute myeloid leukemia cell limes using high-throughput chromosome conformation capture screening.

Tetsuko Kobayashi·Satsuki Matsushima·Hiroaki Ohnishi

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Abstract

Despite advanced molecular diagnostics, improving outcomes for refractory acute myeloid leukemia (AML) remains challenging. Although many cancer-related genes are identified, their molecular mechanisms are not fully elucidated. Amplification is a mechanism of cancer-associated gene activation, and ectopic gene amplification may have particularly high pathological significance. However, research on ectopically amplified cancer-associated genes in leukemia remains limited. Here, we evaluated the usefulness of high-throughput chromosomal conformation capture (Hi-C) as a screening method for ectopic gene amplification and assessed whether ectopic amplification of cancer-associated genes may represent a general phenomenon in AML. We screened the U-937 and NB-4 cell lines using in situ Hi-C. Regions appearing as "high-intensity bands" in Hi-C contact maps were identified and validated using fluorescence in situ hybridization (FISH). Additionally, copy number variation analysis was performed using whole-genome sequencing (WGS) to extract cancer-associated genes with ectopic amplification. In the U-937, three genomic regions showing "high-intensity bands" were identified and confirmed as ectopic amplifications-including PDCD1LG2 (PD-L2), CD274 (PD-L1), and JAK2; that is, four copies were detected by WGS, and amplification signals were observed by FISH. In the NB-4, four such regions were detected, including MYC and KRAS, with expression level of 498 transcripts per million (TPM) and 34 TPM, respectively. Copy number variation analysis further identified multiple cancer-associated genes with ectopic amplification. Overall, these findings demonstrate the presence of ectopic amplification of cancer-associated genes in AML cell lines and support the usefulness of Hi-C as a screening method for detecting such genomic alterations.

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Acute myeloid leukemia Cancer-associated gene Gene amplification In situ high-throughput chromosomal conformation capture KRAS MYC Journal Article

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Tetsuko Kobayashi, Satsuki Matsushima, Hiroaki Ohnishi. 2026-09-05. Identification and characterization of ectopic chromosomal amplifications in acute myeloid leukemia cell limes using high-throughput chromosome conformation capture screening.. https://doi.org/10.1016/j.leukres.2026.108304

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PubMed2026

Machine learning-based integration develops a novel lysosome-related prognostic signature associated with prognosis and immune infiltration landscape in acute myeloid leukemia.

BACKGROUND: Lysosomes are essential for intracellular degradation and recycling, and changes in their function significantly contribute to tumor growth. Nonetheless, the exact role of lysosome-related genes (LRGs) in the pathogenesis of acute myeloid leukemia (AML) is still inadequately comprehended. METHODS: Differentially expressed LRGs (DE-LRGs) between AML and control groups were identified using AML-related data extracted from the Gene Expression Omnibus (GEO). The LRGs-related prognostic genes were identified and the risk model was established using univariate COX regression analysis and machine learning algorithms, based on the data obtained from The Cancer Genome Atlas (TCGA). Subsequently, we performed comprehensive analyses regarding clinical features, functional pathways, immune microenvironment, and chemotherapeutic drugs sensitivity between the high- and low-risk groups. Reverse transcription Quantitative polymerase chain reaction (RT-qPCR) and western blot were adopted to validate the expression of prognostic genes in human bone marrow-derived cell line HS-27 A and human AML cell line MOLM-13. RESULTS: Through comprehensive analysis, a risk model was developed utilizing ten LRGs (ATP6V0E2, CALCRL, TMEM165, GZMB, HCK, TCIRG1, CD1D, GPRASP1, ABCA1, and NAGA), and this model was further validated using GEO datasets. Significant differences in clinical characteristics, functional pathways, immune microenvironment characteristics, and chemotherapeutic drug sensitivity were observed between the two risk groups In vitro validation experiment illustrated that the expression trends of ATP6V0E2, TMEM165, and ABCA1 were consistent with our bioinformatics analysis. CONCLUSION: Our study demonstrates that lysosome-associated signature might forecast the prognosis of AML patients and offer guidance for subsequent immunotherapy and chemotherapy strategies.

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Machine learning-based integration develops a novel lysosome-related prognostic signature associated with prognosis and immune infiltration landscape in acute myeloid leukemia.