Abstract
Introduction: Hematological malignancies are neoplasms that
develop in blood-forming or immune system tissues and are one
of the most common types of tumors in pediatric oncology.
Identification of fusion genes, as one of the most characteristic
structural aberrations in childhood malignancies, contributes to
the development of precision medicine and, thus, effective
methods for treating the disease.
Materials and methods: The longitudinal study enrolled 34
patients, aged 0 to 18 years, with a diagnosis of hematological
malignant tumor. RNA was isolated from whole blood, bone
marrow, or tissue samples, and complementary DNA libraries were
prepared. DNA-seq was performed on the MGI™ DNBSEQ-G400
sequencer. For bioinformatics analysis, QIAGEN CLC Genomics
Workbench v.22.0, DAVID v.2021, Ensembl VEP, and RStudio tools
were used.
Results: In total, 23 459 potential fusion genes were identified,
among them gene fusions that are strongly related to childhood
malignancy initiation, progression, and relapse (ETV6-RUNX1,
KMT2A-AFDN, NTRK3 gene fusion). Identified fusion genes
consisted of 9714 unique genes; most of them were connected
to cancer hallmarks, such as sustaining proliferative signaling,
genome instability, tumor-promoting inflammation, and others.
Conclusion: The largest number of fusion genes is observed in
the group of patients diagnosed with AML. Most genes included
in fusions were responsible for the “cell division” Gene Ontology
process, thus falling into the “Sustaining proliferative signaling”
hallmark category.
Grant References: Funded by the patronage of MikroTik Ltd.
within the framework of the University of Latvia Foundation
project Nr.2242 “Investigation of precision medicine strategies in
the treatment of pediatric malignancies”.
Conflict of Interest: None declared
develop in blood-forming or immune system tissues and are one
of the most common types of tumors in pediatric oncology.
Identification of fusion genes, as one of the most characteristic
structural aberrations in childhood malignancies, contributes to
the development of precision medicine and, thus, effective
methods for treating the disease.
Materials and methods: The longitudinal study enrolled 34
patients, aged 0 to 18 years, with a diagnosis of hematological
malignant tumor. RNA was isolated from whole blood, bone
marrow, or tissue samples, and complementary DNA libraries were
prepared. DNA-seq was performed on the MGI™ DNBSEQ-G400
sequencer. For bioinformatics analysis, QIAGEN CLC Genomics
Workbench v.22.0, DAVID v.2021, Ensembl VEP, and RStudio tools
were used.
Results: In total, 23 459 potential fusion genes were identified,
among them gene fusions that are strongly related to childhood
malignancy initiation, progression, and relapse (ETV6-RUNX1,
KMT2A-AFDN, NTRK3 gene fusion). Identified fusion genes
consisted of 9714 unique genes; most of them were connected
to cancer hallmarks, such as sustaining proliferative signaling,
genome instability, tumor-promoting inflammation, and others.
Conclusion: The largest number of fusion genes is observed in
the group of patients diagnosed with AML. Most genes included
in fusions were responsible for the “cell division” Gene Ontology
process, thus falling into the “Sustaining proliferative signaling”
hallmark category.
Grant References: Funded by the patronage of MikroTik Ltd.
within the framework of the University of Latvia Foundation
project Nr.2242 “Investigation of precision medicine strategies in
the treatment of pediatric malignancies”.
Conflict of Interest: None declared
Original language | English |
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Article number | P13.067.C |
Pages (from-to) | 567-567 |
Number of pages | 1 |
Journal | European Journal of Human Genetics |
Volume | 32 |
Issue number | Suppl.1 |
Publication status | Published - Jan 2024 |
Externally published | Yes |
Event | 56th European Society of Human Genetics (ESHG) Conference - Berlin, Germany Duration: 1 Jun 2024 → 4 Jun 2024 |
Field of Science*
- 3.1 Basic medicine
- 3.2 Clinical medicine
Publication Type*
- 3.3. Publications in conference proceedings indexed in Web of Science and/or Scopus database