Clonal approaches to understanding the impact of mutations on hematologic disease development

Abstract Interrogation of hematopoietic tissue at the clonal level has a rich history spanning over 50 years, and has provided critical insights into both normal and malignant hematopoiesis. Characterization of chromosomes identified some of the first genetic links to cancer with the discovery of chromosomal translocations in association with many hematological neoplasms. The unique accessibility of hematopoietic tissue and the ability to clonally expand hematopoietic progenitors in vitro has provided fundamental insights into the cellular hierarchy of normal hematopoiesis, as well as the functional impact of driver mutations in disease. Transplantation assays in murine models have enabled cellular assessment of the functional consequences of somatic mutations in vivo. Most recently, next-generation sequencing–based assays have shown great promise in allowing multi-“omic” characterization of single cells. Here, we review how clonal approaches have advanced our understanding of disease development, focusing on the acquisition of somatic mutations, clonal selection, driver mutation cooperation, and tumor evolution.

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Reconstructing mutational lineages in breast cancer by multi-patient-targeted single cell DNA sequencing

10.1101/2021.11.16.468877 ◽

2021 ◽

Author(s):

Nicholas Navin ◽

Jake Leighton ◽

Min Hu ◽

Emi Sei ◽

Funda Meric-Bernstam

Keyword(s):

Breast Cancer ◽

Dna Sequencing ◽

Single Cell ◽

Copy Number ◽

Somatic Mutations ◽

Single Cells ◽

Tumor Evolution ◽

Sequencing Method ◽

Genomic Regions ◽

Microfluidics Platform

Single cell DNA sequencing (scDNA-seq) methods are powerful tools for profiling mutations in cancer cells, however most genomic regions characterized in single cells are non-informative. To overcome this issue, we developed a Multi-Patient-Targeted (MPT) scDNA-seq sequencing method. MPT involves first performing bulk exome sequencing across a cohort of cancer patients to identify somatic mutations, which are then pooled together to develop a single custom targeted panel for high-throughput scDNA-seq using a microfluidics platform. We applied MPT to profile 330 mutations across 23,500 cells from 5 TNBC patients, which showed that 3 tumors were monoclonal and 2 tumors were polyclonal. From this data, we reconstructed mutational lineages and identified early mutational and copy number events, including early TP53 mutations that occurred in all five patients. Collectively, our data suggests that MPT can overcome technical obstacles for studying tumor evolution using scDNA-seq by profiling information-rich mutation sites.

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Modeling Prostate Cancer Treatment Responses in the Organoid Era: 3D Environment Impacts Drug Testing

Biomolecules ◽

10.3390/biom11111572 ◽

2021 ◽

Vol 11 (11) ◽

pp. 1572

Author(s):

Annelies Van Hemelryk ◽

Lisanne Mout ◽

Sigrun Erkens-Schulze ◽

Pim J. French ◽

Wytske M. van Weerden ◽

...

Keyword(s):

Prostate Cancer ◽

Treatment Effect ◽

Drug Testing ◽

Nuclear Translocation ◽

Single Cells ◽

Great Promise ◽

Preclinical Research ◽

3D Scaffolds ◽

The Impact

Organoid-based studies have revolutionized in vitro preclinical research and hold great promise for the cancer research field, including prostate cancer (PCa). However, experimental variability in organoid drug testing complicates reproducibility. For example, we observed PCa organoids to be less affected by cabazitaxel, abiraterone and enzalutamide as compared to corresponding single cells prior to organoid assembly. We hypothesized that three-dimensional (3D) organoid organization and the use of various 3D scaffolds impact treatment efficacy. Live-cell imaging of androgen-induced androgen receptor (AR) nuclear translocation and taxane-induced tubulin stabilization was used to investigate the impact of 3D scaffolds, spatial organoid distribution and organoid size on treatment effect. Scaffolds delayed AR translocation and tubulin stabilization, with Matrigel causing a more pronounced delay than synthetic hydrogel as well as incomplete tubulin stabilization. Drug effect was further attenuated the more centrally organoids were located in the scaffold dome. Moreover, cells in the organoid core revealed a delayed treatment effect compared to cells in the organoid periphery, underscoring the impact of organoid size. These findings indicate that analysis of organoid drug responses needs careful interpretation and requires dedicated read-outs with consideration of underlying technical aspects.

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The Role of OMICS Research in Understanding Phenotype Variation in Thalassaemia: The THALAMOSS Project

Thalassemia Reports ◽

10.4081/thal.2014.4877 ◽

2014 ◽

Vol 4 (3) ◽

pp. 81-85

Author(s):

Roberto Gambari

Keyword(s):

Gene Therapy ◽

Globin Gene ◽

B Cell Lymphoma ◽

Great Promise ◽

Product Portfolio ◽

Treatment Regimens ◽

Therapeutic Protocols ◽

The Impact ◽

Novel Therapeutic

The β-thalassaemias are a group of severe and rare anaemias with monogenic inheritance, a complex systemic phenotype and several treatment-related complications, caused by more than 300 mutations of the β-globin gene. Novel therapeutic protocols, most of which are based on still experimental treatments, show great promise but significant variability of success between patients. These strategies include chemical/molecular induction of the endogenous β-like γ-globin gene or the restoration of clinically relevant β-globin levels by gene therapy. A small number of modifiers with significant impact on disease penetrance, severity and efficacy of treatments are known, but most remain elusive. Improvements of existing treatment regimens and optimization and application of novel treatments will critically depend on the characterization of additional disease modifiers and the stratification of patients for customized treatment regimens. This requires extensive analyses based on “OMICS”, an English-language neologism which refer to different but connected fields in molecular biology and biochemistry, such as genomics, transcriptomics, exomics, proteomics, metabolomics. The major objective of OMICS is a collective characterization of pools of biological molecules (gene sequences, transcripts, proteins and protein domains) controlling biological structures, functions and dynamics, including several involved in pathological conditions. One of the most interesting observations of genomics in β-thalassaemias is the association between genomic sequences and high fetal haemoglobin (HbF) levels, in consideration of the fact that high HbF levels are usually associated with milder forms of β-thalassaemia. Related to this issue, is the possibility to predict response to different therapeutic protocols on the basis of genomic analyses. For instance, three major loci (Xmn1-HBG2 single nucleotide polymorphism, HBS1L-MYB intergenic region on chromosome 6q, and BCL11A) contribute to high HbF production. Pharmacogenomic analysis of the effects of hydroxyurea (HU) on HbF production in a collection of β-thalassemia and sickle cell disease (SCD) patients allowed the identification of genomic signatures associated with high HbF. Therefore, it can hypothesized that genomic studies might predict the response of patients to treatments based on hydroxyurea, which is at present the most used HbF inducer in pharmacological therapy of β-thalassaemia. Transcriptomic/proteomic studies allowed to identify the zinc finger transcription factor B-cell lymphoma/leukemia 11A (BCL11A) as the major repressor of HbF expression. The field of research on g-globin gene repressors (including BCL11A) is of top interest, since several approaches can lead to pharmacologically-mediated inhibition of the expression of g-globin gene repressors, leading to gglobin gene activation. Among these strategies, we underline direct targeting of the transcription factors by aptamers or decoy molecules, as well as inhibition of the mRNA coding g-globin gene repressors with shRNAs, antisense molecules, peptide nucleic acids (PNAs) and microRNAs. In this respect, the THALAMOSS FP7 Project (THALAssaemia MOdular Stratification System for personalized therapy of β-thalassemia, www.thalamoss.eu) aims develop a universal sets of markers and techniques for stratification of β-thalassaemia patients into treatment subgroups for (a) onset and frequency of blood transfusions, (b) choice of iron chelation, (c) induction of fetal hemoglobin, (d) prospective efficacy of gene-therapy. The impact of THALAMOSS is the provision of novel biomarkers for distinct treatment subgroups in β-thalassaemia (500–1000 samples from participating medical centres), identified by combined genomics, proteomics, transcriptomics and tissue culture assays, the development of new or improved products for the cell isolation, characterization and treatment of β-thalassaemia patients and the establishment of routine techniques for detection of these markers and stratification of patients into treatment groups. Translation of these activities into the product portfolio and R&D methodology of participating SMEs will be a major boost for them as well as for the field. THALAMOSS tools and technologies will (a) facilitate identification of novel diagnostic tests, drugs and treatments specific to patient subgroups and (b) guide conventional and novel therapeutic approaches for β-thalassaemia, including personalized medical treatments.

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The Impact of Somatic Mutations upon the Response to Combination Therapy with Ruxolitinib and Interferon in MPN Patients

Blood ◽

10.1182/blood-2021-152154 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 3589-3589

Author(s):

Vibe Skov ◽

Anders Lindholm Sørensen ◽

Trine Alma Knudsen ◽

Mads Emil Bjørn ◽

Christina Ellervik ◽

...

Keyword(s):

Combination Therapy ◽

Treatment Response ◽

Allele Frequency ◽

Somatic Mutations ◽

Triple Negative ◽

Median Number ◽

Post Treatment ◽

Driver Mutations ◽

Molecular Response ◽

The Impact

Abstract Introduction: The Philadelphia-negative myeloproliferative neoplasms (MPN) are associated with driver mutations in JAK2, CALR, and MPL genes. Non-driver mutations affect disease progression and treatment response. Combination therapy with pegylated interferon-alpha2 (IFN) and ruxolitinib has recently been shown to induce hematologic and molecular responses in patients (pts) with MPN. We studied 25 pts by targeted next generation sequencing (NGS) of 42 genes and investigated the impact of somatic mutations (mut) on treatment response. Methods: Twenty-five MPN pts with polycythemia vera (PV) (n=16, all JAK2V617F) and myelofibrosis (MF) (n=9, JAK2V617F (6), CALR (1), MPL (1), triple-negative (1)) participated in the study. NGS was performed on the Illumina platform on DNA from peripheral blood at baseline and after 24 months of combination therapy. Data were analyzed using Biomedical Genomics workbench and VarSeq. Variants with coverage <100x, variant allele frequency (VAF) <1%, introns and germline variants, and SNPs with minor allele frequency >1% were excluded. A mut with VAF <1% in either a pre- or post-treatment sample was retained if VAF was >1% in the paired sample. However, a mut with a number of mutated reads below 7 was considered absent. Only pathogenic mut were reported. Statistical analysis was done using either chi-square test or Wilcoxon signed rank/rank sum test in R 4.0.2. A p-value <0.05 was considered significant. The ELN and IWG-MRT response criteria were used. Results: At baseline and 24 months, PV-pts had a mean number of mut of 2.3 and 2.4, and MF-pts 2.2 and 3.0, respectively. In all pts, 0 and 1 (0/4%) patient had no mut, 10 and 7 (40/28%) had 1 mut, 10 and 9 (40/36%) had 2 mut, and 5 and 8 (20/32%) had ≥ 3 mut at baseline and 24 months, respectively. In PV, 1 (6%) achieved CR and 3 (19%) achieved PR and 12 (75%) achieved NR. In MF, 4 (44%) achieved CR and 1 (11%) achieved PR and 4 either NR, PD, SD or CI. There was no association between pts achieving CR/PR or NR and median number of mut at baseline (CR/PR: 1, range 1-3) or (NR: 2, range 1-8), (p=0.28). Excluding driver mut, there was still no significant association. In all JAK2V617F positive pts, the median JAK2V617F allele burden (%JAK2V617F) decreased from 37% (range: 1.9-95) at baseline to 22.5% (range: 0-85) at 24 months. In pts achieving CR or PR (n=7), the reduction in %JAK2V617F was greater (median: 42% to 18%, p<0.05) compared with pts achieving NR (n=12) (median: 30% to 22%, p<0.005). Stratified according to molecular response (MR) (n=4) or non-MR (n=13), median % JAK2V617F at baseline was 40 (21-95) and 43 (42-70) in non-MR and MR, respectively, and 31 (11-85) and 13 (1.8-25) in non-MR and MR, respectively during treatment. At baseline, pts achieving MR had no non-driver mut and pts achieving non-MR had a median number of non-driver mut of 1 (range: 0-7) (p<0.02). Eight pts were not evaluable because they were either CALR or MPL positive, triple-negative, or had a baseline JAK2V617F ≤ 20%. In all pts, there were 30 non-driver mut in 15 genes at baseline and 40 non-driver mut in 19 genes at 24 months of therapy. At baseline and at 24 months, TP53 occurred in 6 and 6 (24%), TET2, ASXL1, RUNX1, or SF3B1 in 2 and 3 (8/12%), and CBL, DNMT3A, or SRSF2 in 2 and 2 (8%) pts, respectively. Eleven new non-driver post-treatment mut occurred in 9 pts and were more prevalent in pts with MF (6/9, 66%) compared to pts with PV (3/16, 19%), p<0.02. However, the VAF was low (median 1.2%, range 1.02% - 3.6%) and none of the new 11 post-treatment mut appeared in the same gene. Discussion and Conclusions: Earlier studies have shown an association between poor response to IFN and number of mut or high molecular risk mut. In this study, the presence of non-driver mut was associated with a significantly poorer molecular response. However, there was no association between the presence or type of non-driver mut and clinico-hematologic response. At 24 months, there was an evolution of subclones with a significantly higher number of new subclones appearing in pts with MF compared to pts with PV. However, the VAF was low and none of the acquired mut appeared in the same gene contradictory to another study showing an association between treatment-emergent mut in DNMT3A and treatment with IFN. In conclusion, these data show that a clinico-hematologic response is achievable during combination therapy despite the presence of non-driver mutations at baseline. Disclosures Bjørn: Novartis: Other: Ruxolitnib. Hasselbalch: Novartis, AOP Orphan: Consultancy, Other: Advisory Board. OffLabel Disclosure: Interferon-alpha for treatment

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In silicolearning of tumor evolution through mutational time series

10.1101/577171 ◽

2019 ◽

Author(s):

Noam Auslander ◽

Yuri I. Wolf ◽

Eugene V. Koonin

Keyword(s):

Neural Network ◽

Time Series ◽

Tumor Progression ◽

Somatic Mutations ◽

Clinical Decision Making ◽

Driver Mutations ◽

Tumor Evolution ◽

Driver Genes ◽

Mutational Burden ◽

Cancer Drivers

AbstractCancer arises through the accumulation of somatic mutations over time. Understanding the sequence of mutation occurrence during cancer progression can assist early and accurate diagnosis and improve clinical decision-making. Here we employ Long Short-Term Memory networks (LSTMs), a class of recurrent neural network, to learn the evolution of a tumor through an ordered sequence of mutations. We demonstrate the capacity of LSTMs to learn complex dynamics of the mutational time series governing tumor progression, allowing accurate prediction of the mutational burden and the occurrence of mutations in the sequence. Using the probabilities learned by the LSTM, we simulate mutational data and show that the simulation results are statistically indistinguishable from the empirical data. We identify passenger mutations that are significantly associated with established cancer drivers in the sequence and demonstrate that the genes carrying these mutations are substantially enriched in interactions with the corresponding driver genes. Breaking the network into modules consisting of driver genes and their interactors, we show that these interactions are associated with poor patient prognosis, thus likely conferring growth advantage for tumor progression. Thus, application of LSTM provides for prediction of numerous additional conditional drivers and to reveal hitherto unknown aspects of cancer evolution.SignificanceCancer is caused by the effects of somatic mutations known as drivers. Although a number of major cancer drivers have been identified, it is suspected that many more comparatively rare and conditional drivers exist, and the interactions between different cancer-associated mutations that might be relevant for tumor progression are not well understood. We applied an advanced neural network approach to learn the sequence of mutations and the mutational burden in colon and lung cancers, and to identify mutations that are associated with individual drivers. A significant ordering of driver mutations is demonstrated, and numerous, previously undetected conditional drivers are identified. These findings broaden the existing understanding of the mechanisms of tumor progression and have implications for therapeutic strategies.

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Examining the Role of CD30 in an Anaplastic Large Cell Lymphoma Mouse Model

Blood ◽

10.1182/blood-2019-125589 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 2542-2542

Author(s):

Teresa Poggio ◽

Linda Graessel ◽

Stefanie Kreutmair ◽

Cornelius Miething ◽

Dietmar Pfeifer ◽

...

Keyword(s):

Immune System ◽

T Cell ◽

Mouse Model ◽

Cell Lymphoma ◽

Large Cell ◽

Disease Development ◽

Large Cell Lymphoma ◽

The Impact

Anaplastic large cell lymphoma (ALCL) represents a heterogeneous group of T-cell non-Hodgkin lymphoma (NHL) mainly affecting children and young adults. About 70% of systemic ALCLs are associated with a characteristic chromosomal translocation, t(2;5)(p23;35) which fuses the anaplastic lymphoma kinase (ALK) gene on chromosome 2 with the nucleophosmin (NPM) gene on chromosome 5, resulting in the NPM-ALK fusion gene, its over-expression and constitutive kinase activity. Immunophenotypic characterization of human ALCL revealed highly CD30-positive cells of T- or Null-Cell-origin and resulted in promising clinical trials with CD30-coupled antibodies. However, the impact of CD30 on disease development remains unclear and the relationship between NPM-ALK and CD30 has been investigated mostly using cell line models. Syngeneic mouse models of cancer can serve as useful models since the tumors develop in situ where the contribution made by the immune system and the extracellular matrix can be investigated. Here, we focus on the involvement of CD30 in a retroviral murine bone marrow transplantation model of ALCL. In this model, the BM of Lck-Cre-transgenic mice is infected with a MSCV-Stop-NPM-ALK-IRES-EGFP vector leading to expression of NPM-ALK in early T-cells. With a latency of 3-4 months, mice develop lymphomas and die from neoplastic T-cell-infiltration of BM and lymphatic organs. To investigate the impact of abrogation of CD30 signals on the development of NPM-ALK+ ALCL in our model, CD30 knockout mice were crossed with Lck-Cre mice. Both Lck-Cre NPM-ALK CD30 wt and Lck-Cre NPM-ALK CD30 ko recipients develop a human ALCL-like lymphoma with a pure T-cell phenotype characterized by Thy1.2+ cells infiltrating the thymus, lymph nodes, spleen and BM. First results from Lck-Cre NPM-ALK CD30 ko transplanted mice showed impaired disease induction and prolonged survival compared to CD30 wt animals. Moreover, secondary transplantation of NPM-ALK thymic lymphomas led to distinct deceleration of disease development upon CD30 deletion. Microarray analyses have shed some light on the mechanisms underlying the delayed lymphoma progression of CD30 deleted tumors with an upregulation of inflammatory pathways and proteins that are master players in inflammation and immune responses. Further characterization of the role of CD30-mediated immune response in disease progression using this mouse model and immunocompromised mice is ongoing. An improved understanding of how the immune system affects tumor progression will extend the rationale in translational strategies to use immunotherapies for patients with T-NHLs. Disclosures No relevant conflicts of interest to declare.

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DoE Analysis of Approaches for Hydrogel Microbeads’ Preparation by Millifluidic Methods

Micromachines ◽

10.3390/mi11111007 ◽

2020 ◽

Vol 11 (11) ◽

pp. 1007

Author(s):

Anna Nastruzzi ◽

Gabriele Pitingolo ◽

Giovanni Luca ◽

Claudio Nastruzzi

Keyword(s):

Mass Production ◽

Large Scale ◽

Single Cells ◽

Great Promise ◽

Scale Production ◽

Large Scale Production ◽

Different Types ◽

Cell Transplants

Hydrogel microbeads hold great promise for immune-protective cell transplants and in vitro studies. Millifluidic generation of hydrogel microbeads is a highly efficient and reproducible approach enabling a mass production. This paper illustrates the preparation and characterization of highly controlled and reproducible microbeads made by different types of hydrogel using millifluidic approaches. The optimization of the process was made by a design of experiments (DoE) approach. The microbeads’ large-scale production can be potentially used for single cells or clusters encapsulation.

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Next-Generation Sequencing: A Discovery Tool for Blood Disorders

Blood ◽

10.1182/blood.v120.21.sci-10.sci-10 ◽

2012 ◽

Vol 120 (21) ◽

pp. SCI-10-SCI-10

Author(s):

Elaine R. Mardis ◽

Li Ding ◽

Peter Westervelt ◽

John S. Welch ◽

Jeffery M. Klco ◽

...

Keyword(s):

Conflicts Of Interest ◽

Massively Parallel Sequencing ◽

Tumor Biology ◽

Cancer Genome ◽

Driver Mutations ◽

Tumor Evolution ◽

Whole Genome ◽

Next Generation ◽

Hematopoietic Stem ◽

The Impact

Abstract Abstract SCI-10 The advent and evolution of next-generation massively parallel sequencing (MPS) has radically altered our approaches to studying the cancer genome and transcriptome. By using unbiased and comprehensive MPS in the context of clinically annotated samples from leukemia cases, rapid progress has resulted in our understanding of the mutational spectrum of hematopoietic malignancies, the heterogeneity of disease presentation, and the impact of chemotherapy on the cancer genome, among others. The complexity of the transcriptome, while daunting from an analytical standpoint, further reveals the nuances of gene expression changes in leukemia that often cannot be predicted simply by studying the genome. By applying the digital nature of MPS to explore tumor heterogeneity and tumor evolution, we have shown that de novo acute myeloid leukemia (AML) presents either as a mono- or multiclonal disease, and that the relapse presentation in the same patient is an evolved genetic derivation of the de novopresentation, often with novel driver mutations that have been acquired during the course of chemotherapy (1). New data from whole genome sequencing of hematopoietic stem cells in healthy volunteers indicates that somatic mutations largely are acquired during aging and occur randomly, carrying forward in the transformed cell. This baseline is important for the further comparison of AML subtypes, and provides a context for understanding tumor biology. Last, by studying 200 AML cases using whole-genome and exome sequencing, RNA-seq, miRNA-seq and array-based methylation, we have begun an integrated characterization of AML in an effort to inform tumor biology. These studies and the accompanying technologies set the stage for precision treatment of each AML patient according to the additional information provided by the person's integrated “omic” profile. Disclosures: No relevant conflicts of interest to declare.

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Improving diagnostic and prognostic accuracy of myeloid neoplasms (MNs) by next generation sequencing.

Journal of Clinical Oncology ◽

10.1200/jco.2017.35.15_suppl.e18567 ◽

2017 ◽

Vol 35 (15_suppl) ◽

pp. e18567-e18567

Author(s):

Candice Schwartz ◽

Jason Nathaniel Macklis ◽

Lela Buckingham ◽

Jamile M. Shammo

Keyword(s):

Rna Splicing ◽

Somatic Mutations ◽

Prognostic Significance ◽

Primary Myelofibrosis ◽

Definitive Diagnosis ◽

Driver Mutations ◽

Or Management ◽

Panel Testing ◽

Gene Panel Testing ◽

The Impact

e18567 Background: Molecular aberrations in MNs have been well described. Driver mutations such as JAK2, MPL, and CALR, are pathognomonic for MNs, whereas other somatic mutations are less specific but have prognostic significance. Multi-gene panel testing for known somatic mutations has been utilized for diagnostic and prognostic purposes, and testing for somatic mutations to identify clonal hematopoiesis has been adopted by the WHO 2016 classification of myeloid malignancies. We sought to assess the impact of testing for somatic mutations by NGS on diagnosis and management of pts with MNs. Methods: We employed a myeloid panel (MP) of 40 commonly mutated genes involving RNA splicing, chromatin remodeling, and signaling pathways. Testing was performed on ptswho presented to the clinic between 2/2015 and 12/2016. Initial diagnosis and rationale for testing (diagnostic or prognostic) were recorded. We then determined whether the MP resulted in a change in diagnosis, prognosis, or management. Results: 55 pts with a known or suspected MN had a MP performed.Diagnoses at presentation were: MDS (27), MF (8), MPN-U (8), MDS/MPN (4), multiple diagnoses (2), and no definitive diagnosis of MN (6). 87% (48/55) of pts had at least one somatic mutation.In 13 pts (23.6%) the MP led to a definitive diagnosis or a change in diagnosis. For example, 2 pts initially diagnosed with MPN-U were diagnosed with CNL after detection of CSF3R mutation. All 4 pts initially diagnosed with MDS with fibrosis were subsequently diagnosed with primary myelofibrosis; 3 had a MPL mutation and 1 had a CALR mutation. Management was altered in 12 pts (21.8%) and prognosis was changed in 11 pts (20.0%). For example, 2 pts were treated with a JAK-2 inhibitor and 2 pts with low risk MDS were referred for transplant evaluation due to the presence of a TP53mutation. Conclusions: Our study confirms that panel testing meaningfully improves diagnostic accuracy and provides prognostic value. In total, the MP resulted in a change in diagnosis, prognosis, or management in 43.6% (24/55) of cases. Confirmation of these observations merits prospective evaluation for a larger number of pts.

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Chromatin reprogramming as an adaptation mechanism in advanced prostate cancer

Endocrine Related Cancer ◽

10.1530/erc-18-0579 ◽

2019 ◽

Vol 26 (4) ◽

pp. R211-R235 ◽

Cited By ~ 6

Author(s):

Peder Rustøen Braadland ◽

Alfonso Urbanucci

Keyword(s):

Prostate Cancer ◽

Drug Resistance ◽

High Throughput Sequencing ◽

Single Cells ◽

Tumor Evolution ◽

Adaptation Mechanism ◽

Associated Proteins ◽

Chromatin Relaxation ◽

Chromatin Reprogramming ◽

The Impact

Tumor evolution is based on the ability to constantly mutate and activate different pathways under the selective pressure of targeted therapies. Epigenetic alterations including those of the chromatin structure are associated with tumor initiation, progression and drug resistance. Many cancers, including prostate cancer, present enlarged nuclei, and chromatin appears altered and irregular. These phenotypic changes are likely to result from epigenetic dysregulation. High-throughput sequencing applied to bulk samples and now to single cells has made it possible to study these processes in unprecedented detail. It is therefore timely to review the impact of chromatin relaxation and increased DNA accessibility on prostate cancer growth and drug resistance, and their effects on gene expression. In particular, we focus on the contribution of chromatin-associated proteins such as the bromodomain-containing proteins to chromatin relaxation. We discuss the consequence of this for androgen receptor transcriptional activity and briefly summarize wider gain-of-function effects on other oncogenic transcription factors and implications for more effective prostate cancer treatment.

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