Bottom-up proteomic analysis of single HCT 116 colon carcinoma multicellular spheroids

Gas-Phase Fractionation Data-Independent Acquisition Analysis of 3D Cocultured Spheroid Tumor Model Reveals Altered Translational Processes and Signaling Using Proteomics

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.

Hybrid-DIA: intelligent data acquisition integrates targeted and discovery proteomics to analyze phospho-signaling in single spheroids

Achieving sufficient coverage of regulatory phosphorylation sites by mass spectrometry (MS)-based phosphoproteomics for signaling pathway reconstitution is challenging, especially when analyzing tiny sample amounts. To address this, we present a hybrid data-independent acquisition (DIA) strategy (hybrid-DIA) that combines targeted and discovery proteomics through an Application Programming Interface (API) to dynamically intercalate DIA scans with accurate triggering of multiplexed tandem mass spectrometry (MSx) scans of predefined (phospho)peptide targets. By spiking-in heavy stable isotope labeled phosphopeptide standards covering seven major signaling pathways, we benchmark hybrid-DIA against state-of-the-art targeted MS methods (i.e., SureQuant) using EGF-stimulated HeLa cells and find the quantitative accuracy and sensitivity to be comparable while hybrid-DIA also profiles the global phosphoproteome. To demonstrate the robustness, sensitivity, and biomedical potential of hybrid-DIA, we profile chemotherapeutic agents in single colon carcinoma multicellular spheroids and evaluate the phospho-signaling difference of cancer cells in 2D vs 3D culture.

Development of Spheroid-FPOP: An In-Cell Protein Footprinting Method for 3D Tumor Spheroids

Many cancer drugs fail at treating solid epithelial tumors with hypoxia and insufficient drug penetration thought to be contributing factors to the observed chemoresistance. Owing to this, it is imperative to evaluate potential cancer drugs in conditions as close to in vivo as possible, which is not always done. To address this, we developed a mass spectrometry-based protein footprinting method for exploring the impact of hypoxia on protein in 3D colorectal cancer cells. Our group has previously extended the protein footprinting method fast photochemical oxidation of proteins (FPOP) for live cell analysis (IC-FPOP); however, this is the first application of IC-FPOP in a 3D cancer model. In this study, we perform IC-FPOP on intact spheroids (Spheroid-FPOP) using a modified version of the static platform incubator with an XY movable stage (PIXY) FPOP platform. We detected modification in each of three spheroid layers, even the hypoxic core. Pathway analysis revealed protein modifications in over 10 distinct protein pathways, including some involved in protein ubiquitination; a process modulated in cancer pathologies. These results demonstrate the feasibility of Spheroid-FPOP to be utilized as a tool to interrogate protein interactions within a native tumor microenvironment.

Metabolic flux analysis of 3D spheroids reveals significant differences in glucose metabolism from matched 2D cultures of colorectal cancer and pancreatic ductal adenocarcinoma cell lines

BACKGROUND

Most in vitro cancer cell experiments have been performed using 2D models. However, 3D spheroid cultures are increasingly favored for being more representative of in vivo tumor conditions. To overcome the translational challenges with 2D cell cultures, 3D systems better model more complex cell-to-cell contact and nutrient levels present in a tumor, improving our understanding of cancer complexity. Despite this need, there are few reports on how 3D cultures differ metabolically from 2D cultures.

METHODS

Well-described cell lines from colorectal cancer (HCT116 and SW948) and pancreatic ductal adenocarcinoma (Panc-1 and MIA-Pa-Ca-2) were used to investigate metabolism in 3D spheroid models. The metabolic variation under normal glucose conditions were investigated comparing 2D and 3D cultures by metabolic flux analysis and expression of key metabolic proteins.

RESULTS

We find significant differences in glucose metabolism of 3D cultures compared to 2D cultures, both related to glycolysis and oxidative phosphorylation. Spheroids have higher ATP-linked respiration in standard nutrient conditions and higher non-aerobic ATP production in the absence of supplemented glucose. In addition, ATP-linked respiration is significantly inversely correlated with OCR/ECAR (p = 0.0096). Mitochondrial transport protein, TOMM20, expression decreases in all spheroid models compared to 2D, and monocarboxylate transporter (MCT) expression increases in 3 of the 4 spheroid models.

CONCLUSIONS

In this study of CRC and PDAC cell lines, we demonstrate that glucose metabolism in 3D spheroids differs significantly from 2D cultures, both in terms of glycolytic and oxidative phosphorylation metrics. The metabolic phenotype shift from 2D to 3D culture in one cell line is greater than the phenotypic differences between each cell line and tumor source. The results herein emphasize the need to use 3D cell models for investigating nutrient utilization and metabolic flux for a better understanding of tumor metabolism and potential metabolic therapeutic targets.

Spatial Stable Isotopic Labeling by Amino Acids in Cell Culture: Pulse-Chase Labeling of Three-Dimensional Multicellular Spheroids for Global Proteome Analysis

Three-dimensional cell cultures, or spheroids, are important model systems for cancer research because they recapitulate chemical and phenotypic aspects of in vivo tumors. Spheroids develop radially symmetric chemical gradients, resulting in distinct cellular populations. Stable isotopic labeling by amino acids in cell culture (SILAC) is a well-established approach to quantify protein expression and has previously been used in a pulse-chase format to evaluate temporal changes. In this article, we demonstrate that distinct isotopic signatures can be introduced into discrete spatial cellular populations, effectively tracking proteins to original locations in the spheroid, using a platform that we refer to as spatial SILAC. Spheroid populations were grown with light, medium, and heavy isotopic media, and the concentric shells of cells were harvested by serial trypsinization. Proteins were quantitatively analyzed by ultraperformance liquid chromatography-tandem mass spectrometry. The isotopic signatures correlated with the spatial location and the isotope position do not significantly impact the proteome of each individual layer. Spatial SILAC can be used to examine the proteomic changes in the different layers of the spheroid and to identify protein biomarkers throughout the structure. We show that SILAC labels can be discretely pulsed to discrete positions, without altering the spheroid's proteome, promising future combined pharmacodynamic and pharmacokinetic studies.

Proteomics of Colorectal Cancer: Tumors, Organoids, and Cell Cultures-A Minireview

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.

Integrated cancer tissue engineering models for precision medicine

Tumors are not merely cancerous cells that undergo mindless proliferation. Rather, they are highly organized and interconnected organ systems. Tumor cells reside in complex microenvironments in which they are subjected to a variety of physical and chemical stimuli that influence cell behavior and ultimately the progression and maintenance of the tumor. As cancer bioengineers, it is our responsibility to create physiologic models that enable accurate understanding of the multi-dimensional structure, organization, and complex relationships in diverse tumor microenvironments. Such models can greatly expedite clinical discovery and translation by closely replicating the physiological conditions while maintaining high tunability and control of extrinsic factors. In this review, we discuss the current models that target key aspects of the tumor microenvironment and their role in cancer progression. In order to address sources of experimental variation and model limitations, we also make recommendations for methods to improve overall physiologic reproducibility, experimental repeatability, and rigor within the field. Improvements can be made through an enhanced emphasis on mathematical modeling, standardized in vitro model characterization, transparent reporting of methodologies, and designing experiments with physiological metrics. Taken together these considerations will enhance the relevance of in vitro tumor models, biological understanding, and accelerate treatment exploration ultimately leading to improved clinical outcomes. Moreover, the development of robust, user-friendly models that integrate important stimuli will allow for the in-depth study of tumors as they undergo progression from non-transformed primary cells to metastatic disease and facilitate translation to a wide variety of biological and clinical studies.

Mass Spectrometry Analyses of Multicellular Tumor Spheroids

Multicellular tumor spheroids (MCTS) are a powerful biological in vitro model, which closely mimics the 3D structure of primary avascularized tumors. Mass spectrometry (MS) has established itself as a powerful analytical tool, not only to better understand and describe the complex structure of MCTS, but also to monitor their response to cancer therapeutics. The first part of this review focuses on traditional mass spectrometry approaches with an emphasis on elucidating the molecular characteristics of these structures. Then the mass spectrometry imaging (MSI) approaches used to obtain spatially defined information from MCTS is described. Finally the analysis of primary spheroids, such as those present in ovarian cancer, and the great potential that mass spectrometry analysis of these structures has for improved understanding of cancer progression and for personalized in vitro therapeutic testing is discussed.

iTRAQ Quantitative Proteomic Profiling and MALDI-MSI of Colon Cancer Spheroids Treated with Combination Chemotherapies in a 3D Printed Fluidic Device

For a patient with metastatic colorectal cancer there are limited clinical options aside from chemotherapy. Unfortunately, the development of new chemotherapeutics is a long and costly process. New methods are needed to identify promising drug candidates earlier in the drug development process. Most chemotherapies are administered to patients in combinations. Here, an in vitro platform is used to assess the penetration and metabolism of combination chemotherapies in three-dimensional colon cancer cell cultures, or spheroids. Colon carcinoma HCT 116 cells were cultured and grown into three-dimensional cell culture spheroids. These spheroids were then dosed with a common combination chemotherapy, FOLFIRI (folinic acid, 5-fluorouracil, and irinotecan) in a 3D printed fluidic device. This fluidic device allows for the dynamic treatment of spheroids across a semipermeable membrane. Following dosing, the spheroids were harvested for quantitative proteomic profiling to examine the effects of the combination chemotherapy on the colon cancer cells. Spheroids were also imaged to assess the spatial distribution of administered chemotherapeutics and metabolites with MALDI-imaging mass spectrometry. Following treatment, we observed penetration of folinic acid to the core of spheroids and metabolism of the drug in the outer proliferating region of the spheroid. Proteomic changes identified included an enrichment of several cancer-associated pathways. This innovative dosing device, along with the proteomic evaluation with iTRAQ-MS/MS, provides a robust platform that could have a transformative impact on the preclinical evaluation of drug candidates. This system is a high-throughput and cost-effective approach to examine novel drugs and drug combinations prior to animal testing.

Multicellular Tumor Spheroids Combined with Mass Spectrometric Histone Analysis To Evaluate Epigenetic Drugs

Multicellular tumor spheroids (MCTS) are valuable in vitro tumor models frequently used to evaluate the penetration and efficacy of therapeutics. In this study, we evaluated potential differences in epigenetic markers, i.e., histone post-translational modifications (PTMs), in the layers of the HCT116 colon carcinoma MCTS. Cells were grown in agarose-coated 96 well plates, forming reproducible 1-mm-diameter MCTS. The MCTS were fractionated into three radially concentric portions, generating samples containing cells from the core, the mid and the external layers. Using mass spectrometry (MS)-based proteomics and EpiProfile, we quantified hundreds of histone peptides in different modified forms; by combining the results of all experiments, we quantified the abundance of 258 differently modified peptides, finding significant differences in their relative abundance across layers. Among these differences, we detected higher amounts of the repressive mark H3K27me3 in the external layers, compared to the core. We then evaluated the epigenetic response of MCTS following UNC1999 treatment, a drug targeting the enzymes that catalyze H3K27me3, namely, the polycomb repressive complex 2 (PRC2) subunits enhancer of zeste 1 (EZH1) and enhancer of zeste 2 (EZH2). UNC1999 treatment resulted in significant differences in MCTS diameter under drug treatment of varying duration. Using matrix-assisted laser desorption/ionization (MALDI) imaging, we determined that the drug penetrates the entire MCTS. Proteomic analysis revealed a decrease in abundance of H3K27me3, compared to the untreated sample, as expected. Interestingly, we observed a comparable growth curve for MCTS under constant drug treatment over 13 days with those treated for only 4 days at the beginning of their growth. We thus demonstrate that MS-based proteomics can define significant differences in histone PTM patterns in submillimetric layers of three-dimensional (3D) cultures. Moreover, we show that our model is suitable for monitoring drug localization and regulation of histone PTMs after drug treatment.

Quantitative Proteomic and Phosphoproteomic Comparison of 2D and 3D Colon Cancer Cell Culture Models

Cell cultures are widely used model systems. Some immortalized cell lines can be grown in either two-dimensional (2D) adherent monolayers or in three-dimensional (3D) multicellular aggregates, or spheroids. Here, the quantitative proteome and phosphoproteome of colon carcinoma HT29 cells cultures in 2D monolayers and 3D spheroids were compared with a stable isotope labeling of amino acids (SILAC) labeling strategy. Two biological replicates from each sample were examined, and notable differences in both the proteome and the phosphoproteome were determined by nanoliquid chromatography tandem mass spectrometry (LC-MS/MS) to assess how growth configuration affects molecular expression. A total of 5867 protein groups, including 2523 phosphoprotein groups and 8733 phosphopeptides were identified in the samples. The Gene Ontology analysis revealed enriched GO terms in the 3D samples for RNA binding, nucleic acid binding, enzyme binding, cytoskeletal protein binding, and histone binding for their molecular functions (MF) and in the process of cell cycle, cytoskeleton organization, and DNA metabolic process for the biological process (BP). The KEGG pathway analysis indicated that 3D cultures are enriched for oxidative phosphorylation pathways, metabolic pathways, peroxisome pathways, and biosynthesis of amino acids. In contrast, analysis of the phosphoproteomes indicated that 3D cultures have decreased phosphorylation correlating with slower growth rates and lower cell-to-extracellular matrix interactions. In sum, these results provide quantitative assessments of the effects on the proteome and phosphoproteome of culturing cells in 2D versus 3D cell culture configurations.

Proteomic challenges: sample preparation techniques for microgram-quantity protein analysis from biological samples

Proteins regulate many cellular functions and analyzing the presence and abundance of proteins in biological samples are central focuses in proteomics. The discovery and validation of biomarkers, pathways, and drug targets for various diseases can be accomplished using mass spectrometry-based proteomics. However, with mass-limited samples like tumor biopsies, it can be challenging to obtain sufficient amounts of proteins to generate high-quality mass spectrometric data. Techniques developed for macroscale quantities recover sufficient amounts of protein from milligram quantities of starting material, but sample losses become crippling with these techniques when only microgram amounts of material are available. To combat this challenge, proteomicists have developed micro-scale techniques that are compatible with decreased sample size (100 μg or lower) and still enable excellent proteome coverage. Extraction, contaminant removal, protein quantitation, and sample handling techniques for the microgram protein range are reviewed here, with an emphasis on liquid chromatography and bottom-up mass spectrometry-compatible techniques. Also, a range of biological specimens, including mammalian tissues and model cell culture systems, are discussed.