Modeling chromosomal translocations using conditional alleles to recapitulate initiating events in human leukemias

Emerging In Vitro and In Vivo Models: Hope for the Better Understanding of Cancer Progression and Treatment

Various cancer models have been developed to aid the understanding of the underlying mechanisms of tumor development and evaluate the effectiveness of various anticancer drugs in preclinical studies. These models accurately reproduce the critical stages of tumor initiation and development to mimic the tumor microenvironment better. Using these models for target validation, tumor response evaluation, resistance modeling, and toxicity comprehension can significantly enhance the drug development process. Herein, various in vivo or animal models are presented, typically consisting of several mice and in vitro models ranging in complexity from transwell models to spheroids and CRISPR-Cas9 technologies. While in vitro models have been used for decades and dominate the early stages of drug development, they are still limited primary to simplistic tests based on testing on a single cell type cultivated in Petri dishes. Recent advancements in developing new cancer therapies necessitate the generation of complicated animal models that accurately mimic the tumor's complexity and microenvironment. Mice make effective tumor models as they are affordable, have a short reproductive cycle, exhibit rapid tumor growth, and are simple to manipulate genetically. Human cancer mouse models are crucial to understanding the neoplastic process and basic and clinical research improvements. The following review summarizes different in vitro and in vivo metastasis models, their advantages and disadvantages, and their ability to serve as a model for cancer research.

p160 nuclear receptor coactivator family members and their role in rare fusion‑driven neoplasms (Review)

Gene fusions with translocations involving nuclear receptor coactivators (NCoAs) are relatively common among fusion-driven malignancies. NCoAs are essential mediators of environmental cues and can modulate the transcription of downstream target genes upon binding to activated nuclear receptors. Therefore, fusion proteins containing NCoAs can become strong oncogenic drivers, affecting the cell transcriptional profile. These tumors show a strong dependency on the fusion oncogene; therefore, the direct pharmacological targeting of the fusion protein becomes an attractive strategy for therapy. Currently, different combinations of chemotherapy regimens are used to treat a variety of NCoA-fusion-driven tumors, but given the frequent tumor reoccurrence, more efficient treatment strategies are needed. Specific approaches directed towards inhibition or silencing of the fusion gene need to be developed while minimizing the interference with the original genes. This review highlights the relevant literature describing the normal function and structure of NCoAs and their oncogenic activity in NCoA-gene fusion-driven cancers, and explores potential strategies that could be effective in targeting these fusions.

Specificity of cancer-related chromosomal translocations is linked to proximity after the DNA double-strand break and subsequent selection

Most cancer-related chromosomal translocations appear to be cell type specific. It is currently unknown why different chromosomal translocations occur in different cells. This can be due to either the occurrence of particular translocations in specific cell types or adaptive survival advantage conferred by translocations only in specific cells. We experimentally addressed this question by double-strand break (DSB) induction at MYC, IGH, AML and ETO loci in the same cell to generate chromosomal translocations in different cell lineages. Our results show that any translocation can potentially arise in any cell type. We have analyzed different factors that could affect the frequency of the translocations, and only the spatial proximity between gene loci after the DSB induction correlated with the resulting translocation frequency, supporting the 'breakage-first' model. Furthermore, upon long-term culture of cells with the generated chromosomal translocations, only oncogenic MYC-IGH and AML-ETO translocations persisted over a 60-day period. Overall, the results suggest that chromosomal translocation can be generated after DSB induction in any type of cell, but whether the cell with the translocation would persist in a cell population depends on the cell type-specific selective survival advantage that the chromosomal translocation confers to the cell.

Decoding Oncofusions: Unveiling Mechanisms, Clinical Impact, and Prospects for Personalized Cancer Therapies

Cancer-associated gene fusions, also known as oncofusions, have emerged as influential drivers of oncogenesis across a diverse range of cancer types. These genetic events occur via chromosomal translocations, deletions, and inversions, leading to the fusion of previously separate genes. Due to the drastic nature of these mutations, they often result in profound alterations of cellular behavior. The identification of oncofusions has revolutionized cancer research, with advancements in sequencing technologies facilitating the discovery of novel fusion events at an accelerated pace. Oncofusions exert their effects through the manipulation of critical cellular signaling pathways that regulate processes such as proliferation, differentiation, and survival. Extensive investigations have been conducted to understand the roles of oncofusions in solid tumors, leukemias, and lymphomas. Large-scale initiatives, including the Cancer Genome Atlas, have played a pivotal role in unraveling the landscape of oncofusions by characterizing a vast number of cancer samples across different tumor types. While validating the functional relevance of oncofusions remains a challenge, even non-driver mutations can hold significance in cancer treatment. Oncofusions have demonstrated potential value in the context of immunotherapy through the production of neoantigens. Their clinical importance has been observed in both treatment and diagnostic settings, with specific fusion events serving as therapeutic targets or diagnostic markers. However, despite the progress made, there is still considerable untapped potential within the field of oncofusions. Further research and validation efforts are necessary to understand their effects on a functional basis and to exploit the new targeted treatment avenues offered by oncofusions. Through further functional and clinical studies, oncofusions will enable the advancement of precision medicine and the drive towards more effective and specific treatments for cancer patients.

Identifying the oncogenic potential of gene fusions exploiting miRNAs

It is estimated that oncogenic gene fusions cause about 20% of human cancer morbidity. Identifying potentially oncogenic gene fusions may improve affected patients' diagnosis and treatment. Previous approaches to this issue included exploiting specific gene-related information, such as gene function and regulation. Here we propose a model that profits from the previous findings and includes the microRNAs in the oncogenic assessment. We present ChimerDriver, a tool to classify gene fusions as oncogenic or not oncogenic. ChimerDriver is based on a specifically designed neural network and trained on genetic and post-transcriptional information to obtain a reliable classification. The designed neural network integrates information related to transcription factors, gene ontologies, microRNAs and other detailed information related to the functions of the genes involved in the fusion and the gene fusion structure. As a result, the performances on the test set reached 0.83 f1-score and 96% recall. The comparison with state-of-the-art tools returned comparable or higher results. Moreover, ChimerDriver performed well in a real-world case where 21 out of 24 validated gene fusion samples were detected by the gene fusion detection tool Starfusion. ChimerDriver integrates transcriptional and post-transcriptional information in an ad-hoc designed neural network to effectively discriminate oncogenic gene fusions from passenger ones. ChimerDriver source code is freely available at https://github.com/martalovino/ChimerDriver.

Challenges and Opportunities in NUT Carcinoma Research

NUT carcinoma (NC) is a type of aggressive cancer driven by chromosome translocations. Fusion genes between a DNA-binding protein, such as bromodomain and extraterminal domain (BET) proteins, and the testis-specific protein NUTM1 generated by these translocations drive the formation of NC. NC can develop in very young children without significant accumulation of somatic mutations, presenting a relatively clean model to study the genetic etiology of oncogenesis. However, after 20 years of research, a few challenging questions still remain for understanding the mechanism and developing therapeutics for NC. In this short review, we first briefly summarize the current knowledge regarding the molecular mechanism and targeted therapy development of NC. We then raise three challenging questions: (1) What is the cell of origin of NC? (2) How does the germline analogous epigenetic reprogramming process driven by the BET-NUTM1 fusion proteins cause NC? and (3) How will BET-NUTM1 targeted therapies be developed? We propose that with the unprecedented technological advancements in genome editing, animal models, stem cell biology, organoids, and chemical biology, we have unique opportunities to address these challenges.

Glioblastomas harboring gene fusions detected by next-generation sequencing

Oncogenic gene fusions have been reported in diffuse gliomas and may serve as potential therapeutic targets. Here, using next-generation sequencing analysis (Illumina TruSight Tumor 170 panel), we analyzed a total of 356 diffuse gliomas collected from 2017 to 2019 to evaluate clinical, pathological, and genetic features of gene fusion. We found 53 cases of glioblastomas harboring the following oncogenic gene fusions: MET (n = 18), EGFR (n = 14), FGFR (n = 12), NTRK (n = 5), RET (n = 2), AKT3 (n = 1), and PDGFRA fusions (n = 1). Gene fusions were consistently observed in both IDH-wildtype and IDH-mutant glioblastomas (8.8% and 9.4%, p = 1.000). PTPRZ1-MET fusion was the only fusion that genetically resembled secondary glioblastomas (i.e., high frequency of IDH mutation, ATRX loss, TP53 mutation, and absence of EGFR amplification), whereas other gene fusion types were similar to primary glioblastomas (i.e., high frequency of IDH-wildtype, TERT mutation, EGFR amplification, and PTEN mutation). In IDH-wildtype glioblastoma patients, multivariable analysis revealed that the PTPRZ1-MET fusion was associated with poor progression-free survival (HR [95% CI]: 5.42 (1.72-17.05), p = 0.004). Additionally, we described two novel cases of CCDC6-RET fusion in glioma. Collectively, our findings indicate that targetable gene fusions are associated with aggressive biological behavior and can aid the clinical treatment strategy for glioma patients.

MLLT10 in benign and malignant hematopoiesis

Non-random chromosomal translocations involving the putative transcription factor Mixed Lineage Leukemia Translocated to 10 (MLLT10, also known as AF10) are commonly observed in both acute myeloid and lymphoid leukemias and are indicative of a poor prognosis. Despite the well-described actions of oncogenic MLLT10 fusion proteins, the role of wild-type MLLT10 in hematopoiesis is not well characterized. The protein structure and several interacting partners have been described and provide indications as to the potential functions of MLLT10. This review examines these aspects of MLLT10, contextualizing its function in benign and malignant hematopoiesis.

Towards quantitative and multiplexed in vivo functional cancer genomics

Large-scale sequencing of human tumours has uncovered a vast array of genomic alterations. Genetically engineered mouse models recapitulate many features of human cancer and have been instrumental in assigning biological meaning to specific cancer-associated alterations. However, their time, cost and labour-intensive nature limits their broad utility; thus, the functional importance of the majority of genomic aberrations in cancer remains unknown. Recent advances have accelerated the functional interrogation of cancer-associated alterations within in vivo models. Specifically, the past few years have seen the emergence of CRISPR-Cas9-based strategies to rapidly generate increasingly complex somatic alterations and the development of multiplexed and quantitative approaches to ascertain gene function in vivo.

Molecular Signatures of Fusion Proteins in Cancer

Although gene fusions are recognized as driver mutations in a wide variety of cancers, the general molecular mechanisms underlying oncogenic fusion proteins are insufficiently understood. Here, we employ large-scale data integration and machine learning and (1) identify three functionally distinct subgroups of gene fusions and their molecular signatures; (2) characterize the cellular pathways rewired by fusion events across different cancers; and (3) analyze the relative importance of over 100 structural, functional, and regulatory features of ∼2200 gene fusions. We report subgroups of fusions that likely act as driver mutations and find that gene fusions disproportionately affect pathways regulating cellular shape and movement. Although fusion proteins are similar across different cancer types, they affect cancer type-specific pathways. Key indicators of fusion-forming proteins include high and nontissue specific expression, numerous splice sites, and higher centrality in protein-interaction networks. Together, these findings provide unifying and cancer type-specific trends across diverse oncogenic fusion proteins.

Molecular Principles of Gene Fusion Mediated Rewiring of Protein Interaction Networks in Cancer

Gene fusions are common cancer-causing mutations, but the molecular principles by which fusion protein products affect interaction networks and cause disease are not well understood. Here, we perform an integrative analysis of the structural, interactomic, and regulatory properties of thousands of putative fusion proteins. We demonstrate that genes that form fusions (i.e., parent genes) tend to be highly connected hub genes, whose protein products are enriched in structured and disordered interaction-mediating features. Fusion often results in the loss of these parental features and the depletion of regulatory sites such as post-translational modifications. Fusion products disproportionately connect proteins that did not previously interact in the protein interaction network. In this manner, fusion products can escape cellular regulation and constitutively rewire protein interaction networks. We suggest that the deregulation of central, interaction-prone proteins may represent a widespread mechanism by which fusion proteins alter the topology of cellular signaling pathways and promote cancer.

Three-dimensional ex vivo co-culture models of the leukaemic bone marrow niche for functional drug testing

Acute myeloid leukaemia (AML) is a hierarchically structured malignancy in which aberrant leukemic stem cells drive the production of leukaemic blast cell clones. AML cells strictly depend on the bone marrow microenvironment (BMM) in which they reside. Classical AML cell cultures fail to mimic the BMM and, therefore, drug discovery studies are dominated by in vivo models. However, animal models are time consuming, labour intensive, provide limited mechanistic insight, and are unsuited for high-throughput studies, necessitating the development of novel AML models. The evolving ex vivo BMM-mimicking culture systems aim to fill this gap, with increasing success. Here, we discuss how AML-microenvironment co-culture models advance our understanding of this disease, and highlight their future potential for translational AML research.

Discovering and understanding oncogenic gene fusions through data intensive computational approaches

Although gene fusions have been recognized as important drivers of cancer for decades, our understanding of the prevalence and function of gene fusions has been revolutionized by the rise of next-generation sequencing, advances in bioinformatics theory and an increasing capacity for large-scale computational biology. The computational work on gene fusions has been vastly diverse, and the present state of the literature is fragmented. It will be fruitful to merge three camps of gene fusion bioinformatics that appear to rarely cross over: (i) data-intensive computational work characterizing the molecular biology of gene fusions; (ii) development research on fusion detection tools, candidate fusion prioritization algorithms and dedicated fusion databases and (iii) clinical research that seeks to either therapeutically target fusion transcripts and proteins or leverages advances in detection tools to perform large-scale surveys of gene fusion landscapes in specific cancer types. In this review, we unify these different-yet highly complementary and symbiotic-approaches with the view that increased synergy will catalyze advancements in gene fusion identification, characterization and significance evaluation.

Applying a Weight-of-Evidence Approach to Evaluate Relevance of Molecular Landscapes in the Exposure-Disease Paradigm

Information on polymorphisms, mutations, and epigenetic events has become increasingly important in our understanding of molecular mechanisms associated with exposures-disease outcomes. Molecular landscapes can be developed to illustrate the molecular characteristics for environmental carcinogens as well as associated disease outcomes, although comparison of these molecular landscapes can often be difficult to navigate. We developed a method to organize these molecular data that uses a weight-of-evidence approach to rank overlapping molecular events by relative importance for susceptibility to an exposure-disease paradigm. To illustrate the usefulness of this approach, we discuss the example of benzene as an environmental carcinogen and myelodysplastic syndrome (MDS) as a causative disease endpoint. Using this weight-of-evidence method, we found overlapping polymorphisms in the genes for the metabolic enzymes GST and NQO1, both of which may infer risk of benzene-induced MDS. Polymorphisms in the tumor suppressor gene, TP53, and the inflammatory cytokine gene, TNF-α, were also noted, albeit inferring opposing outcomes. The alleles identified in the DNA repair gene RAD51 indicated an increased risk for MDS in MDS patients and low blood cell counts in benzene-exposed workers. We propose the weight-of-evidence approach as a tool to assist in organizing the sea of emerging molecular data in exposure-disease paradigms.

Human embryonic stem cells carrying an unbalanced translocation demonstrate impaired differentiation into trophoblasts: an in vitro model of human implantation failure

Carriers of the balanced translocation t(11;22), the most common reciprocal translocation in humans, are at high risk of creating gametes with unbalanced translocation, leading to repeated miscarriages. Current research models for studying translocated embryos and the biological basis for their implantation failure are limited. The aim of this study was to elucidate whether human embryonic stem cells (hESCs) carrying the unbalanced chromosomal translocation t(11;22) can provide an explanation for repeated miscarriages of unbalanced translocated embryos. Fluorescent in situ hybridization and karyotype analysis were performed to analyze the t(11;22) in embryos during PGD and in the derived hESC line. The hESC line was characterized by RT-PCR and FACS analysis for pluripotent markers. Directed differentiation to trophoblasts was carried out by bone morphogenetic protein 4 (BMP4). Trophoblast development was analyzed by measuring β-hCG secretion, by β-hCG immunostaining and by gene expression of trophoblastic markers. We derived the first hESC line carrying unbalanced t(11;22), which showed the typical morphological and molecular characteristics of a hESC line. Control hESCs differentiated into trophoblasts secreted increasing levels of β-hCG and concomitantly expressed the trophoblast genes, CDX2, TP63, KRT7, ERVW1, CGA, GCM1, KLF4 and PPARG. In contrast, differentiated translocated hESCs displayed reduced and delayed secretion of β-hCG concomitant with impaired expression of the trophoblastic genes. The reduced activation of trophoblastic genes may be responsible for the impaired trophoblastic differentiation in t(11;22)-hESCs, associated with implantation failure in unbalanced t(11;22) embryos. Our t(11;22) hESCs are presented as a valuable human model for studying the mechanisms underlying implantation failure.

How does DNA break during chromosomal translocations?

Chromosomal translocations are one of the most common types of genetic rearrangements and are molecular signatures for many types of cancers. They are considered as primary causes for cancers, especially lymphoma and leukemia. Although many translocations have been reported in the last four decades, the mechanism by which chromosomes break during a translocation remains largely unknown. In this review, we summarize recent advances made in understanding the molecular mechanism of chromosomal translocations.

Advances in understanding benzene health effects and susceptibility

Benzene is a ubiquitous chemical in our environment that causes acute leukemia and probably other hematological cancers. Evidence for an association with childhood leukemia is growing. Exposure to benzene can lead to multiple alterations that contribute to the leukemogenic process, indicating a multimodal mechanism of action. Research is needed to elucidate the different roles of multiple metabolites in benzene toxicity and the pathways that lead to their formation. Studies to date have identified a number of polymorphisms in candidate genes that confer susceptibility to benzene hematotoxicity. However, a genome-wide study is needed to truly assess the role of genetic variation in susceptibility. Benzene affects the blood-forming system at low levels of occupational exposure, and there is no evidence of a threshold. There is probably no safe level of exposure to benzene, and all exposures constitute some risk in a linear, if not supralinear, and additive fashion.

Genetically engineered mouse models in cancer research

Mouse models of human cancer have played a vital role in understanding tumorigenesis and answering experimental questions that other systems cannot address. Advances continue to be made that allow better understanding of the mechanisms of tumor development, and therefore the identification of better therapeutic and diagnostic strategies. We review major advances that have been made in modeling cancer in the mouse and specific areas of research that have been explored with mouse models. For example, although there are differences between mice and humans, new models are able to more accurately model sporadic human cancers by specifically controlling timing and location of mutations, even within single cells. As hypotheses are developed in human and cell culture systems, engineered mice provide the most tractable and accurate test of their validity in vivo. For example, largely through the use of these models, the microenvironment has been established to play a critical role in tumorigenesis, since tumor development and the interaction with surrounding stroma can be studied as both evolve. These mouse models have specifically fueled our understanding of cancer initiation, immune system roles, tumor angiogenesis, invasion, and metastasis, and the relevance of molecular diversity observed among human cancers. Currently, these models are being designed to facilitate in vivo imaging to track both primary and metastatic tumor development from much earlier stages than previously possible. Finally, the approaches developed in this field to achieve basic understanding are emerging as effective tools to guide much needed development of treatment strategies, diagnostic strategies, and patient stratification strategies in clinical research.

MLL gene fusions in human leukaemias: in vivo modelling to recapitulate these primary tumourigenic events

Recurrent reciprocal chromosomal translocations are frequently found in leukaemias and sarcomas as initiating events in these cancers. Mouse models of chromosomal translocations are not only important for the elucidation of the mechanism of these factors underlying the disease but are also important pre-clinical models for assessing new drug combinations, developing new rational therapeutic strategies based on new drugs and testing novel macromolecular drugs. We describe three technologies for creating chromosomal translocation mimics in mice, applied specifically to understand how the MLL-fusions contribute to leukaemia. An important finding of this work is that the lineage of the tumours can be controlled by the MLL-protein fusion. The translocation mimic methods can be applied to any human reciprocal chromosomal translocation.