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Shannon AE, Boos CE, Searle BC, Hummon AB. Gas-Phase Fractionation Data-Independent Acquisition Analysis of 3D Cocultured Spheroid Tumor Model Reveals Altered Translational Processes and Signaling Using Proteomics. J Proteome Res 2024; 23:3188-3199. [PMID: 38412258 PMCID: PMC11296903 DOI: 10.1021/acs.jproteome.3c00786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/29/2024]
Abstract
Colorectal cancer (CRC) contains considerable heterogeneity; therefore, models of the disease must also reflect the multifarious components. Compared to traditional 2D models, 3D cellular models, such as tumor spheroids, have the utility to determine the drug efficacy of potential therapeutics. Monoculture spheroids are well-known to recapitulate gene expression, cell signaling, and pathophysiological gradients of avascularized tumors. However, they fail to mimic the stromal cell influence present in CRC, which is known to perturb drug efficacy and is associated with metastatic, late-stage colorectal cancer. This study seeks to develop a cocultured spheroid model using carcinoma and noncancerous fibroblast cells. We characterized the proteomic profile of cocultured spheroids in comparison to monocultured spheroids using data-independent acquisition with gas-phase fractionation. Specifically, we determined that proteomic differences related to translation and mTOR signaling are significantly increased in cocultured spheroids compared to monocultured spheroids. Proteins related to fibroblast function, such as exocytosis of coated vesicles and secretion of growth factors, were significantly differentially expressed in the cocultured spheroids. Finally, we compared the proteomic profiles of both the monocultured and cocultured spheroids against a publicly available data set derived from solid CRC tumors. We found that the proteome of the cocultured spheroids more closely resembles that of the patient samples, indicating their potential as tumor mimics.
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Affiliation(s)
- Ariana E Shannon
- Ohio State Biochemistry Program, The Ohio State University, Columbus, Ohio 43210, United States
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
- Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, United States
- Pelotonia Institute for Immuno-Oncology, The Ohio State University, Columbus, Ohio 43210, United States
| | - Claire E Boos
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
| | - Brian C Searle
- Ohio State Biochemistry Program, The Ohio State University, Columbus, Ohio 43210, United States
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
- Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio 43210, United States
- Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, United States
- Pelotonia Institute for Immuno-Oncology, The Ohio State University, Columbus, Ohio 43210, United States
| | - Amanda B Hummon
- Ohio State Biochemistry Program, The Ohio State University, Columbus, Ohio 43210, United States
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
- Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, United States
- Pelotonia Institute for Immuno-Oncology, The Ohio State University, Columbus, Ohio 43210, United States
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Holbrook JH, Kemper GE, Hummon AB. Quantitative mass spectrometry imaging: therapeutics & biomolecules. Chem Commun (Camb) 2024; 60:2137-2151. [PMID: 38284765 PMCID: PMC10878071 DOI: 10.1039/d3cc05988j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 01/22/2024] [Indexed: 01/30/2024]
Abstract
Mass spectrometry imaging (MSI) has become increasingly utilized in the analysis of biological molecules. MSI grants the ability to spatially map thousands of molecules within one experimental run in a label-free manner. While MSI is considered by most to be a qualitative method, recent advancements in instrumentation, sample preparation, and development of standards has made quantitative MSI (qMSI) more common. In this feature article, we present a tailored review of recent advancements in qMSI of therapeutics and biomolecules such as lipids and peptides/proteins. We also provide detailed experimental considerations for conducting qMSI studies on biological samples, aiming to advance the methodology.
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Affiliation(s)
- Joseph H Holbrook
- Ohio State Biochemistry Program, The Ohio State University, Columbus, Ohio 43210, USA.
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Gabrielle E Kemper
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Amanda B Hummon
- Ohio State Biochemistry Program, The Ohio State University, Columbus, Ohio 43210, USA.
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
- Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, USA
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Lindhorst PH, Hummon AB. Proteomics of Colorectal Cancer: Tumors, Organoids, and Cell Cultures-A Minireview. Front Mol Biosci 2020; 7:604492. [PMID: 33363210 PMCID: PMC7758474 DOI: 10.3389/fmolb.2020.604492] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 11/20/2020] [Indexed: 12/14/2022] Open
Abstract
Proteomics, the study of the complete protein composition of a sample, is an important field for cancer research. Changes in the proteome can serve as a biomarker of cancer or lead to the development of a targeted therapy. This minireview will focus on mass spectrometry-based proteomics studies applied specifically to colorectal cancer, particularly the variety of cancer model systems used, including tumor samples, two-dimensional (2D) and three-dimensional (3D) cell cultures such as spheroids and organoids. A thorough discussion of the application of these systems will accompany the review of the literature, as each provides distinct advantages and disadvantages for colorectal cancer research. Finally, we provide conclusions and future perspectives for the application of these model systems to cancer research as a whole.
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Affiliation(s)
- Philip H Lindhorst
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH, United States
| | - Amanda B Hummon
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH, United States.,The Comprehensive Cancer Center, The Ohio State University, Columbus, OH, United States
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