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Biomedicines
Special Issues
Advances in Genetic Research and Molecular Diagnostics for Hematological Diseases
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Advances in Genetic Research and Molecular Diagnostics for Hematological Diseases

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Molecular Genetics and Genetic Diseases".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 833

Special Issue Editors

Dr. Ying S. Zou

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Guest Editor
Department of Pathology and Genomic Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
Interests: clinical cytogenomic; molecular genetics; cancer biomarkers
Dr. Leonard N. Yenwongfai

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Guest Editor
Department of Pathology, Division of Hematopathology, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
Interests: hematologic malignancies; advanced genomic profiling techniques; computational pathology

Special Issue Information

Dear Colleagues,

This Special Issue is dedicated to exploring cutting-edge genetic research in hematological diseases, with a particular emphasis on both malignant and benign disorders, encompassing inherited and acquired conditions. The complex genetic landscape of these diseases poses significant challenges, underscoring the need for innovative technological approaches to advance our understanding and improve therapeutic outcomes.

Recent advancements in molecular diagnostic techniques—such as next-generation sequencing (NGS), CRISPR gene editing, microarray analysis, optical genome mapping, whole genome sequencing, long-read sequencing, whole transcriptomes, proteomics, digital pathology, and computational intelligence, particularly the use of deep convolutional neural networks (DCNNs)—have revolutionized diagnostic and treatment approaches in hematology. This issue will highlight key research that uncovers the genetic mechanisms driving a range of hematological conditions, including leukemias, lymphomas, and other benign disorders.

This Special Issue will focus on the practical application of advanced molecular methodologies and digital technologies in clinical settings. By highlighting their effectiveness in enhancing diagnostic accuracy and guiding treatment strategies, the issue aims to foster the integration of genetic insights into personalized medicine, ultimately advancing patient care and management in the context of hematological disorders.

Dr. Ying S. Zou
Dr. Leonard N. Yenwongfai
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomedicines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • hematological diseases
  • genetic research
  • benign hematology
  • inherited disorders
  • next-generation sequencing/long-read sequencing
  • optical genome mapping
  • transcriptome
  • proteomics
  • digital pathology
  • deep convolutional neural networks

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

17 pages, 4142 KiB  
Article
Acute Myeloid Leukemia Genome Characterization Study and Subtype Classification Employing Feature Selection and Bayesian Networks
by Zhenzhen Li, Jingwen Li, Sifan Li, Yangyang Wang and Jihan Wang
Biomedicines 2025, 13(5), 1067; https://doi.org/10.3390/biomedicines13051067 - 28 Apr 2025
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Abstract
Background: The precise diagnosis and classification of acute myeloid leukemia (AML) has important implications for clinical management and medical research. Methods: We investigated the expression of protein-coding genes in blood samples from AML patients and controls using The Cancer Genome Atlas (TCGA) and [...] Read more.
Background: The precise diagnosis and classification of acute myeloid leukemia (AML) has important implications for clinical management and medical research. Methods: We investigated the expression of protein-coding genes in blood samples from AML patients and controls using The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. Subsequently, we applied the feature selection method of the least absolute shrinkage and selection operator (LASSO) to select the optimal gene subset for classifying AML patients and controls as well as between a particular FAB subtype and other subtypes of AML. Results: Using LASSO method, we identified a subset of 101 genes that could effectively distinguish between AML patients and control individuals; these genes included 70 up-regulated and 31 down-regulated genes in AML. Functional annotation and pathway analysis indicated the involvement of these genes in RNA-related pathways, which was also consistent with the epigenetic changes observed in AML. Results from survival analysis revealed that several genes are correlated with the overall survival in AML patients. Additionally, LASSO-based gene subset analysis successfully revealed differences between certain AML subtypes, providing valuable insights into subtype-specific molecular mechanisms and differentiation therapy. Conclusions: This study demonstrated the application of machine learning in genomic data analysis for identifying gene subsets relevant to AML diagnosis and classification, which could aid in improving the understanding of the molecular landscape of AML. The identification of survival-related genes and subtype-specific markers may lead to the identification of novel targets for personalized medicine in the treatment of AML. Full article
(This article belongs to the Special Issue Advances in Genetic Research and Molecular Diagnostics for Hematological Diseases)
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18 pages, 2132 KiB  
Article
Functional Role of Fatty Acid Synthase for Signal Transduction in Core-Binding Factor Acute Myeloid Leukemia with an Activating c-Kit Mutation
by Ruimeng Zhuang, Bente Siebels, Konstantin Hoffer, Anna Worthmann, Stefan Horn, Nikolas Christian Cornelius von Bubnoff, Cyrus Khandanpour, Niklas Gebauer, Sivahari Prasad Gorantla, Hanna Voss, Hartmut Schlüter, Malte Kriegs, Walter Fiedler, Carsten Bokemeyer, Manfred Jücker and Maxim Kebenko
Biomedicines 2025, 13(3), 619; https://doi.org/10.3390/biomedicines13030619 - 3 Mar 2025
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Abstract
Background/Objectives: Acute myeloid leukemia (AML) is a rare hematological malignancy with a poor prognosis. Activating c-Kit (CD117) mutations occur in 5% of de novo AML and 30% of core-binding factor (CBF) AML, leading to worse clinical outcomes. Posttranslational modifications, particularly with myristic [...] Read more.
Background/Objectives: Acute myeloid leukemia (AML) is a rare hematological malignancy with a poor prognosis. Activating c-Kit (CD117) mutations occur in 5% of de novo AML and 30% of core-binding factor (CBF) AML, leading to worse clinical outcomes. Posttranslational modifications, particularly with myristic and palmitic acid, are crucial for various cellular processes, including membrane organization, signal transduction, and apoptosis regulation. However, most research has focused on solid tumors, with limited understanding of these mechanisms in AML. Fatty acid synthase (FASN), a key palmitoyl-acyltransferase, regulates the subcellular localization, trafficking, and degradation of target proteins, such as H-Ras, N-Ras, and FLT3-ITDmut receptors in AML. Methods: In this study, we investigated the role of FASN in two c-Kit-N822K-mutated AML cell lines using FASN knockdown via shRNA and the FASN inhibitor TVB-3166. Functional implications, including cell proliferation, were assessed through Western blotting, mass spectrometry, and PamGene. Results: FASN inhibition led to an increased phosphorylation of c-Kit (p-c-Kit), Lyn kinase (pLyn), MAP kinase (pMAPK), and S6 kinase (pS6). Furthermore, we observed sustained high expression of Gli1 in Kasumi1 cells following FASN inhibition, which is well known to be mediated by the upregulation of pS6. Conclusions: The combination of TVB-3166 and the Gli inhibitor GANT61 resulted in a significant reduction in the survival of Kasumi1 cells. Full article
(This article belongs to the Special Issue Advances in Genetic Research and Molecular Diagnostics for Hematological Diseases)
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