Emerging Opportunities for Target Discovery in Rare Cancers

Sharifnia, Tanaz; Hong, Andrew L.; Painter, Corrie; Boehm, Jesse S.

doi:10.1016/j.chembiol.2017.08.002

Cited by 40 publications

(24 citation statements)

References 169 publications

(191 reference statements)

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“…CR technology, one of the highly significant milestones in generation of these high-quality laboratory models, allows rapid propagation of cells obtained from patients. [21][22][23]26 It relies on the use of ROCK inhibitor, Y-27632, typically in combination with feeder cells, to induce cell proliferation. 21 In normal cells, CR induces an adult stem-like state.…”

Section: Discussionmentioning

confidence: 99%

“…21 This technology, an epitome of personalized medicine, is currently considered to be a highly significant advance in patient-derived cancer models. [22][23][24][25] CR allows establishing cell lines from human tumors and normal tissues and growing them indefinitely without genetic alterations. 26 The induction of CR is rapid and results from reprogramming of the cell population rather than clonal selection, as is the case with conventional cell lines.…”

Section: Introductionmentioning

confidence: 99%

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Murine neuroblastoma cell lines developed by conditional reprogramming preserve heterogeneous phenotypes observed in vivo

Krawczyk

Hong

Galli

et al. 2020

Laboratory Investigation

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Neuroblastoma (NB) is a pediatric tumor of the peripheral nervous system. Treatment of the disease represents an unsolved clinical problem, as survival of patients with aggressive form of NB remains below 50%. Despite recent identification of numerous potential therapeutic targets, clinical trials validating them are challenging due to rarity of the disease and its high patient-topatient heterogeneity. Hence, there is a need for the accurate preclinical models that would allow testing novel therapeutic approaches and prioritizing the clinical studies, preferentially in personalized way. Here, we propose using conditional reprogramming (CR) technology for rapid development of primary NB cell cultures that could become a new model for such tests. This newly established method allowed for indefinite propagation of normal and tumor cells of epithelial origin in an undifferentiated state by their culture in the presence of Rho-associated kinase (ROCK) inhibitor, Y-27632, and irradiated mouse feeder cells. Using a modification of this approach, we isolated cell lines from tumors arising in the TH-MYCN murine transgenic model of NB (CR-NB). The cells were positive for neuronal markers, including Phox2B and peripherin and consisted of two distinct populations: mesenchymal and adrenergic expressing corresponding markers of their specific lineage. This heterogeneity of the CR-NB cells mimicked the different tumor cell phenotypes in TH-MYCN tumor tissues. The CR-NB cells preserved anchorageindependent growth capability and were successfully passaged, frozen and biobanked. Further studies are required to determine the utility of this method for isolation of human NB cultures, which can become a novel model for basic, translational and clinical research, including individualized drug testing. Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Murine neuroblastoma cell lines developed by conditional reprogramming preserve heterogeneous phenotypes observed in vivo

Krawczyk

Hong

Galli

et al. 2020

Laboratory Investigation

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“…However, diagnostic entities are evolving rapidly, making consistent case identification difficult and confounding attempts at systematic data collection. Molecular sub-classification can be further extended to include host factors such as expression of immune markers and cell infiltrates, which are of great interest because of the emergence of immunotherapies [26].…”

Section: The Biology Of Rare Cancermentioning

confidence: 99%

Evidence-based data and rare cancers: The need for a new methodological approach in research and investigation

Mathoulin‐Pélissier

Pritchard‐Jones

2019

European Journal of Surgical Oncology

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Rare cancers are not so rare, their incidence is increasing and, as a group, they have worse survival than the common cancers. These factors emphasise the societal need to ensure sufficient focus on research into their biological basis, aetiological factors, new more effective therapies and organisation of healthcare to improve access to best practice and innovation. Accuracy of diagnosis is one of the first hurdles to be overcome, with around one third of tumours being reclassified - by type or risk group - when subject to a centralised pathology review process. Timely access to appropriate expert knowledge is a second challenge for patients - in Europe this is being addressed by the establishment of European Reference Networks (ERNs) as part of the EU cross border healthcare initiative. There are ERNs for adult solid and haematological cancers and childhood cancers, all of which are individually rare. These ERNs will facilitate creation of large databases of rare tumours that will incorporate knowledge of their molecular features and build an evidence base for the effectiveness of innovative, biology-directed therapies. With an increasing focus on 'real world' outcome data, research methodologies are evolving, to include randomised registry trials and data linkage approaches that exploit the ever-richer information held on patients in routine health care data. The inclusion of genomic analysis into cancer diagnosis, treatment and risk prediction raises many issues for the conduct of clinical research and cohort studies and personal data sharing. Sophisticated means of pseudonymisation, together with full involvement of affected and 'at risk' patients, are supporting novel research designs and access to data that will continue to build the evidence base to improve outcomes for patients with rare cancers.

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“…The clinical applicability of results derived from cancer cell lines remains an important question, however, due in large part to uncertainty as to how well they represent the biological characteristics and drug responses of patient tumors. Historically-derived cell line models likely represent an incomplete sampling of the spectrum of human cancers 6,7 . Many existing models have been propagated for decades in vitro, with factors such as clonal selection, cell culture conditions, and ongoing genomic instability all potentially contributing to systematic differences between cell line models and tumors [7][8][9] .…”

Section: Introductionmentioning

confidence: 99%

Global computational alignment of tumor and cell line transcriptional profiles

Warren

Jones

Shibue

et al. 2020

Preprint

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Cell lines are key tools for preclinical cancer research, but it remains unclear how well they represent patient tumor samples. Identifying cell line models that best represent the features of particular tumor samples, as well as tumor types that lack in vitro model representation, remain important challenges. Gene expression has been shown to provide rich information that can be used to identify tumor subtypes, as well as predict the genetic dependencies and chemical vulnerabilities of cell lines. However, direct comparisons of tumor and cell line transcriptional profiles are complicated by systematic differences, such as the presence of immune and stromal cells in tumor samples and differences in the cancer-type composition of cell line and tumor expression datasets. To address these challenges, we developed an unsupervised alignment method (Celligner) and applied it to integrate several large-scale cell line and tumor RNA-Seq datasets. While our method aligns the majority of cell lines with tumor samples of the same cancer type, it also reveals large differences in tumor/cell line similarity across disease types. Furthermore, Celligner identifies a distinct group of several hundred cell lines from diverse lineages that present a more mesenchymal and undifferentiated transcriptional state and which exhibit distinct chemical and genetic dependencies. This method could thus be used to guide the selection of cell lines that more closely resemble patient tumors and improve the clinical translation of insights gained from cell line models.

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Emerging Opportunities for Target Discovery in Rare Cancers

Cited by 40 publications

References 169 publications

Murine neuroblastoma cell lines developed by conditional reprogramming preserve heterogeneous phenotypes observed in vivo

Murine neuroblastoma cell lines developed by conditional reprogramming preserve heterogeneous phenotypes observed in vivo

Evidence-based data and rare cancers: The need for a new methodological approach in research and investigation

Global computational alignment of tumor and cell line transcriptional profiles

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