Dataset Information

Innate Genetic Evolution of Lung Cancers and Spatial Heterogeneity: Analysis of Treatment-Naive Lesions.

ABSTRACT: INTRODUCTION:Data regarding the pre-treatment intertumor heterogeneity of potential biomarkers in advanced-stage lung cancers is limited. A finding of such heterogeneity between primary and metastatic lesions would prove valuable to determine if a metastatic lesion can be a surrogate for the primary tumor, as more biomarkers will likely be used in the future to inform treatment decisions. METHODS:We performed RNA sequencing to analyze intertumor heterogeneity in 30 specimens (primary tumors, intrathoracic, and extrathoracic metastatic lesions) obtained from five treatment-naïve lung cancer patients. RESULTS:The global unsupervised clustering analysis showed that the lesions clustered at the individual patient level rather than on the metastatic sites, suggesting that the characteristics of specific tumor cells have a greater impact on the gene expression signature than the microenvironment in which the metastasis develops. The mutational and transcriptional data highlight the presence of intertumor heterogeneity showing that the primary tumors are usually distinct from metastatic lesions. Through a comparison between metastatic lesions and the primary tumors, we observed that pathways related to cell proliferation were upregulated, whereas immune-related pathways were downregulated in metastatic lesions. CONCLUSION:These data not only provide insight into the evolution of lung cancers, but also imply possibilities and limitations of biomarker-based treatment in lung cancers.

SUBMITTER: Suda K

PROVIDER: S-EPMC6153034 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Innate Genetic Evolution of Lung Cancers and Spatial Heterogeneity: Analysis of Treatment-Naïve Lesions.

Suda Kenichi K Kim Jihye J Murakami Isao I Rozeboom Leslie L Shimoji Masaki M Shimizu Shigeki S Rivard Christopher J CJ Mitsudomi Tetsuya T Tan Aik-Choon AC Hirsch Fred R FR

Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer 20180619 10

<h4>Introduction</h4>Data regarding the pre-treatment intertumor heterogeneity of potential biomarkers in advanced-stage lung cancers is limited. A finding of such heterogeneity between primary and metastatic lesions would prove valuable to determine if a metastatic lesion can be a surrogate for the primary tumor, as more biomarkers will likely be used in the future to inform treatment decisions.<h4>Methods</h4>We performed RNA sequencing to analyze intertumor heterogeneity in 30 specimens (prim ...[more]

PMID: 29933065

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Project description:Intracellular spatial heterogeneity is frequently observed in bacteria, where the chromosome occupies part of the cell's volume and a circuit's DNA often localizes within the cell. How this heterogeneity affects core processes and genetic circuits is still poorly understood. In fact, commonly used ordinary differential equation (ODE) models of genetic circuits assume a well-mixed ensemble of molecules and, as such, do not capture spatial aspects. Reaction-diffusion partial differential equation (PDE) models have been only occasionally used since they are difficult to integrate and do not provide mechanistic understanding of the effects of spatial heterogeneity. In this paper, we derive a reduced ODE model that captures spatial effects, yet has the same dimension as commonly used well-mixed models. In particular, the only difference with respect to a well-mixed ODE model is that the association rate constant of binding reactions is multiplied by a coefficient, which we refer to as the binding correction factor (BCF). The BCF depends on the size of interacting molecules and on their location when fixed in space and it is equal to unity in a well-mixed ODE model. The BCF can be used to investigate how spatial heterogeneity affects the behavior of core processes and genetic circuits. Specifically, our reduced model indicates that transcription and its regulation are more effective for genes located at the cell poles than for genes located on the chromosome. The extent of these effects depends on the value of the BCF, which we found to be close to unity. For translation, the value of the BCF is always greater than unity, it increases with mRNA size, and, with biologically relevant parameters, is substantially larger than unity. Our model has broad validity, has the same dimension as a well-mixed model, yet it incorporates spatial heterogeneity. This simple-to-use model can be used to both analyze and design genetic circuits while accounting for spatial intracellular effects.

Dataset Information

Innate Genetic Evolution of Lung Cancers and Spatial Heterogeneity: Analysis of Treatment-Naive Lesions.

Publications

Innate Genetic Evolution of Lung Cancers and Spatial Heterogeneity: Analysis of Treatment-Naïve Lesions.

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