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Functional Genomics Identifies Metabolic Vulnerabilities in Pancreatic Cancer [RNA-Seq]

ABSTRACT: Purpose: Modeling microenvironmental influences in cell culture has been challenging, and technical limitations have hampered the comprehensive study of tumor-specific metabolism in vivo. To systematically interrogate metabolic vulnerabilities in PDA, we employed parallel CRISPR-Cas9 genetic screens using both in vivo and in vitro model systems. Methods: 2D culture collected 3 days after plating grown in DMEM, 10%fbs, 1%p/s. 3D culture collected 3 days after plating grown in DMEM, 10%fbs, 1% p/s, 5% matrigel. Tumors were collected from orthotopic injections collected at endpoint of experiment. Results: This work revealed striking overlap of in vivo metabolic dependencies with those in vitro, validating that standard 2D culture conditions are a reliable system for studying cancer metabolism. Moreover, we identified that intercellular nutrient sharing can mask cancer dependencies in pooled screening experiments, highlighting an important limitation of this approach to study tumor metabolism Conclusions: Our work demonstrates the power of genetic screening approaches to define the compendium of in vivo metabolic dependencies in PDA and highlights critical metabolic pathways that may have therapeutic utility.

ORGANISM(S): Mus musculus

PROVIDER: GSE158657 | GEO | 2020/10/01

REPOSITORIES: GEO

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Functional Genomics Identifies Metabolic Vulnerabilities in Pancreatic Cancer [CRISPR Screen]

Project description:Purpose: Modeling microenvironmental influences in cell culture has been challenging, and technical limitations have hampered the comprehensive study of tumor-specific metabolism in vivo. To systematically interrogate metabolic vulnerabilities in PDA, we employed parallel CRISPR-Cas9 genetic screens using both in vivo and in vitro model systems. Methods: A custom library of lentiviral vectors encoding ~18,000 sgRNAs targeting ~3,000 mouse metabolic genes and performed CRISPR-Cas9 screens using a C/57BL6 (B6) mouse pancreatic cancer cell line derived from a KrasG12D-driven autochthonous PDA model. After transduction and selection, parallel screens were performed by in vitro passage or tumor implantation subcutaneously into the flanks of syngeneic hosts. Genomic DNA was then harvaested in vitro after 7 passages (21 days in culture) and in vivo 21 days after implantation. Results: This work revealed striking overlap of in vivo metabolic dependencies with those in vitro, validating that standard 2D culture conditions are a reliable system for studying cancer metabolism. Moreover, we identified that intercellular nutrient sharing can mask cancer dependencies in pooled screening experiments, highlighting an important limitation of this approach to study tumor metabolism Conclusions:Our work demonstrates the power of genetic screening approaches to define the compendium of in vivo metabolic dependencies in PDA and highlights critical metabolic pathways that may have therapeutic utility.

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High-throughput 3D screening reveals differences in drug sensitivities between culture models of JIMT1 breast cancer cells.

Project description:The traditional method for studying cancer in vitro is to grow immortalized cancer cells in two-dimensional (2D) monolayers on plastic. However, many cellular features are impaired in these unnatural conditions and big alterations in gene expression in comparison to tumors have been reported. Three-dimensional (3D) cell culture models have become increasingly popular and are suggested to be better models than 2D monolayers due to improved cell-to-cell contacts and structures that resemble in vivo architecture. The aim of this study was to develop a simple high-throughput 3D drug screening method and to compare drug responses in JIMT1 breast cancer cells when grown in 2D, in polyHEMA coated anchorage independent 3D models and in Matrigel on-top 3D cell culture models. We screened 102 compounds with multiple concentrations and biological replicates for their effects on cell proliferation. The cells were either treated immediately upon plating or they were allowed to grow in 3D for four days prior to the drug treatment. Big variations in drug responses were observed between the models indicating that comparisons of culture model influenced drug sensitivities cannot be made based on effects of a single drug. However, we show with the 63 most prominent drugs that, in general, JIMT1 cells grown on Matrigel were significantly more sensitive to drugs than cells grown in 2D cultures, while responses of cells grown in polyHEMA resembled those of 2D. Furthermore, comparison of gene expression profiles of the cell culture models to xenograft tumors indicated that cells cultured in Matrigel and as xenografts most closely resembled each other. In this study we also suggest that 3D cultures can provide a platform for systematic experimentation of larger compound collections in a high-throughput mode and be used as alternatives for traditional 2D screens towards better comparability to in vivo state.

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