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| Home > Publications database > Therapy Resistance Mechanisms in Hematological Malignancies. |
| Journal Article (Review Article) | DKFZ-2022-01796 |
; ;
2023
Wiley-Liss
Bognor Regis
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Please use a persistent id in citations: doi:10.1002/ijc.34243
Abstract: Hematologic malignancies are model diseases for understanding neoplastic transformation and serve as prototypes for developing effective therapies. Indeed, the concept of systemic cancer therapy originated in hematologic malignancies and has guided the development of chemotherapy, cellular therapies, immunotherapy, and modern precision oncology. Despite significant advances in the treatment of leukemias, lymphomas and multiple myelomas, treatment resistance associated with molecular and clinical relapse remains very common. Therapy of relapsed and refractory disease remains extremely difficult, and failure of disease control at this stage remains the leading cause of mortality in patients with hematologic malignancies. In recent years, many efforts have been made to identify the genetic and epigenetic mechanisms that drive the development of hematologic malignancies to the stage of full-blown disease requiring clinical intervention. In contrast, the mechanisms responsible for treatment resistance in hematologic malignancies remain poorly understood. For example, the molecular characteristics of therapy-resistant persisting cells in minimal residual disease (MRD) remain rather elusive. In this mini-review we want to discuss that cellular heterogeneity and plasticity, together with adaptive genetic and epigenetic processes, lead to reduced sensitivity to various treatment regimens such as chemotherapy and pathway inhibitors such as tyrosine kinase inhibitors. However, resistance mechanisms may be conserved across biologically distinct cancer entities. Recent technological advances have made it possible to explore the underlying mechanisms of therapy resistance with unprecedented resolution and depth. These include novel multi-omics technologies with single cell resolution combined with advanced biocomputational approaches, along with artificial intelligence (AI), and sophisticated disease models for functional validation. This article is protected by copyright. All rights reserved.
Keyword(s): Hematological malignancies ; Mechanisms ; Resistance ; Therapy
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