High-throughput screening in colorectal cancer tissue-originated spheroids.
Ontology highlight
ABSTRACT:
SUBMITTER: Kondo J
PROVIDER: S-EPMC6317944 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The development of new anti-cancer therapeutic agents is necessary to improve antitumor efficacy and reduce toxicities. Here we report using a systematic anticancer drug screening approach we developed previously, to concurrently screen colon and glioma cancer cell lines for 2000 compounds with known bioactivity and 1920 compounds with unknown activity. The hits specific to each tumor cell line were then selected, and further tested with the same cells transfected with EGFP (Enhanced Green Fluorescent Protein) alone. By comparing the percentage of signal reduction from the same cells transfected with the sensor-conjugated reporter system; hits preferably causing apoptosis were identified. Among the known lead compounds, many cardiac glycosides used as cardiotonic drugs were found to effectively and specifically kill colon cancer cells, while statins (hypolipidemic agents) used as cholesterol lowering drugs were relatively more effective in killing glioma cells.
| S-EPMC6947929 | biostudies-literature
Project description:Drug combinations have been proposed to combat drug resistance, but putative treatments are challenged by low bench-to-bed translational efficiency. To explore the effect of cell culture format and readout methods on identification of synergistic drug combinations in vitro, we studied response to 21 clinically relevant drug combinations in standard planar (2D) layouts and physiologically more relevant spheroid (3D) cultures of HCT-116, HT-29 and SW-620 cells. By assessing changes in viability, confluency and spheroid size, we were able to identify readout- and culture format-independent synergies, as well as synergies specific to either culture format or readout method. In particular, we found that spheroids, compared to 2D cultures, were generally both more sensitive and showed greater synergistic response to combinations involving a MEK inhibitor. These results further shed light on the importance of including more complex culture models in order to increase the efficiency of drug discovery pipelines.
| S-EPMC7360566 | biostudies-literature
Project description:Prostate-specific antigen (PSA) is the most frequently used biomarker for the screening of prostate cancer. Understanding the structure of cancer-specific glycans can help us improve PSA assay. In the present study, we analysed the glycans of PSA obtained from culture medium containing cancer tissue-originated spheroids (CTOS) which have similar characteristics as that of the parent tumour to explore the new candidates for cancer-related glycoforms of PSA. The glycan profile of PSA from CTOS was determined by comparing with PSA from normal seminal plasma and cancer cell lines (LNCaP and 22Rv1) using lectin chromatography and mass spectrometry. PSA from CTOS was mostly sialylated and the content of Wisteria floribunda agglutinin reactive glycan (LacdiNAc) was similar to that of PSA derived from seminal plasma and 22Rv1. Conversely, concanavalin A (Con A)-unbound PSA was definitely detected from the three cancer origins but was almost negligible in seminal PSA. Two novel types of PSA were elucidated in the Con A-unbound fraction: one is a high molecular weight PSA with highly branched N-glycans, and the other is a low molecular weight PSA without N-glycans. Furthermore, the existence of Lewis X antigen group on PSA was indicated. These PSAs will be candidates for new cancer-related markers.
| S-EPMC7026178 | biostudies-literature
Project description:Micro-RNAs (miRNAs) are potent regulators of gene expression and cellular phenotype. Each miRNA has the potential to target hundreds of transcripts within the cell thus controlling fundamental cellular processes such as survival and proliferation. Here, we exploit this important feature of miRNA networks to discover vulnerabilities in cancer phenotype, and map miRNA-target relationships across different cancer types. More specifically, we report the results of a functional genomics screen of 1280 miRNA mimics and inhibitors in eight cancer cell lines, and its presentation in a sophisticated interactive data portal. This resource represents the most comprehensive survey of miRNA function in oncology, incorporating breast cancer, prostate cancer and neuroblastoma. A user-friendly web portal couples this experimental data with multiple tools for miRNA target prediction, pathway enrichment analysis and visualization. In addition, the database integrates publicly available gene expression and perturbation data enabling tailored and context-specific analysis of miRNA function in a particular disease. As a proof-of-principle, we use the database and its innovative features to uncover novel determinants of the neuroblastoma malignant phenotype.
| S-EPMC5728403 | biostudies-other
Project description:Tissue microarray (TMA) core images are a treasure trove for artificial intelligence applications. However, a common problem of TMAs is multiple sectioning, which can change the content of the intended tissue core and requires re-labelling. Here, we investigate different ensemble methods for colorectal tissue classification using high-throughput TMAs. Hematoxylin and Eosin (H&E) core images of 0.6 mm or 1.0 mm diameter from three international cohorts were extracted from 54 digital slides (n = 15,150 cores). After TMA core extraction and color enhancement, five different flows of independent and ensemble deep learning were applied. Training and testing data with 2144 and 13,006 cores included three classes: tumor, normal or "other" tissue. Ground-truth data were collected from 30 ngTMA slides (n = 8689 cores). A test augmentation is applied to reduce the uncertain prediction. Predictive accuracy of the best method, namely Soft Voting Ensemble of one VGG and one CapsNet models was 0.982, 0.947 and 0.939 for normal, "other" and tumor, which outperformed to independent or ensemble learning with one base-estimator. Our high-accuracy algorithm for colorectal tissue classification in high-throughput TMAs is amenable to images from different institutions, core sizes and stain intensity. It helps to reduce error in TMA core evaluations with previously given labels.
| S-EPMC7840737 | biostudies-literature
Project description:BACKGROUND: Organotypic tumor spheroids, a 3D in vitro model derived from patient tumor material, preserve tissue heterogeneity and retain structural tissue elements, thus replicating the in vivo tumor more closely than commonly used 2D and 3D cell line models. Such structures harbour tumorigenic cells, as revealed by xenograft implantation studies in animal models and maintain the genetic makeup of the original tumor material. The aim of our work was a morphological and proteomic characterization of organotypic spheroids derived from colorectal cancer tissue in order to get insight into their composition and associated biology. RESULTS: Morphological analysis showed that spheroids were of about 250 ?m in size and varied in structure, while the spheroid cells differed in shape and size and were tightly packed together by desmosomes and tight junctions. Our proteomic data revealed significant alterations in protein expression in organotypic tumor spheroids cultured as primary explants compared to primary colorectal cancer tissue. Components underlying cellular and tissue architecture were changed; nuclear DNA/ chromatin maintenance systems were up-regulated, whereas various mitochondrial components were down-regulated in spheroids. Most interestingly, the mesenchymal cells appear to be substantial component in such cellular assemblies. Thus the observed changes may partly occur in this cellular compartment. Finally, in the proteomics analysis stem cell-like characteristics were observed within the spheroid cellular assembly, reflected by accumulation of Alcam, Ctnnb1, Aldh1, Gpx2, and CD166. These findings were underlined by IHC analysis of Ctnnb1, CD24 and CD44, therefore warranting closer investigation of the tumorigenic compartment in this 3D culture model for tumor tissue. CONCLUSIONS: Our analysis of organotypic CRC tumor spheroids has identified biological processes associated with a mixture of cell types and states, including protein markers for mesenchymal and stem-like cells. This 3D tumor model in which tumor heterogeneity is preserved may represent an advantageous model system to investigate novel therapeutic approaches.
| S-EPMC4114130 | biostudies-other
Project description:Targeted intracellular delivery of biomolecules and therapeutic cargo enables the controlled manipulation of cellular processes. Laser-based optoporation has emerged as a versatile, non-invasive technique that employs light-based transient physical disruption of the cell membrane and achieves high transfection efficiency with low cell damage. Testing of the delivery efficiency of optoporation-based techniques has been conducted on single cells in monolayers, but its applicability in three-dimensional (3D) cell clusters/spheroids has not been explored. Cancer cells grown as 3D tumor spheroids are widely used in anti-cancer drug screening and can be potentially employed for testing delivery efficiency. Towards this goal, we demonstrated the optoporation-based high-throughput intracellular delivery of a model fluorescent cargo (propidium iodide, PI) within 3D SiHa human cervical cancer spheroids. To enable this technique, nano-spiked core-shell gold-coated polystyrene nanoparticles (ns-AuNPs) with a high surface-to-volume ratio were fabricated. ns-AuNPs exhibited high electric field enhancement and highly localized heating at an excitation wavelength of 680 nm. ns-AuNPs were co-incubated with cancer cells within hanging droplets to enable the rapid aggregation and assembly of spheroids. Nanosecond pulsed-laser excitation at the optimized values of laser fluence (45 mJ cm-2), pulse frequency (10 Hz), laser exposure time (30 s), and ns-AuNP concentration (5 × 1010 particles per ml) resulted in the successful delivery of PI dye into cancer cells. This technique ensured high delivery efficiency (89.6 ± 2.8%) while maintaining high cellular viability (97.4 ± 0.4%), thereby validating the applicability of this technique for intracellular delivery. The optoporation-based strategy can enable high-throughput single cell manipulation, is scalable towards larger 3D tissue constructs, and may provide translational benefits for the delivery of anti-cancer therapeutics to tumors.
| S-EPMC7611397 | biostudies-literature
Project description:This paper presents a new 3D culture microtechnology for high throughput production of tumor spheroids and validates its utility for screening anti-cancer drugs. We use two immiscible polymeric aqueous solutions and microprint a submicroliter drop of the "patterning" phase containing cells into a bath of the "immersion" phase. Selecting proper formulations of biphasic systems using a panel of biocompatible polymers results in the formation of a round drop that confines cells to facilitate spontaneous formation of a spheroid without any external stimuli. Adapting this approach to robotic tools enables straightforward generation and maintenance of spheroids of well-defined size in standard microwell plates and biochemical analysis of spheroids in situ, which is not possible with existing techniques for spheroid culture. To enable high throughput screening, we establish a phase diagram to identify minimum cell densities within specific volumes of the patterning drop to result in a single spheroid. Spheroids show normal growth over long-term incubation and dose-dependent decrease in cellular viability when treated with drug compounds, but present significant resistance compared to monolayer cultures. The unprecedented ease of implementing this microtechnology and its robust performance will benefit high throughput studies of drug screening against cancer cells with physiologically-relevant 3D tumor models.
| S-EPMC4233147 | biostudies-literature
Project description:Cell and protein arrays have demonstrated remarkable utility in the high-throughput evaluation of biological responses; however, they lack the complexity of native tissue and organs. Here we spotted tissue extracellular matrix (ECM) particles as two-dimensional (2D) arrays or incorporated them with cells to generate three-dimensional (3D) cell-matrix microtissue arrays. We then investigated the responses of human stem, cancer and immune cells to tissue ECM arrays originating from 11 different tissues. We validated the 2D and 3D arrays as representative of the in vivo microenvironment by means of quantitative analysis of tissue-specific cellular responses, including matrix production, adhesion and proliferation, and morphological changes after culture. The biological outputs correlated with tissue proteomics, and network analysis identified several proteins linked to cell function. Our methodology enables broad screening of ECMs to connect tissue-specific composition with biological activity, providing a new resource for biomaterials research and further understanding of regeneration and disease mechanisms.
| S-EPMC4666781 | biostudies-literature
Project description:The purpose of this study is to identify protein kinase genes that modulate oxaliplatin cytotoxicity in vitro and evaluate the roles of these genes in predicting clinical outcomes in CRC patients receiving oxaliplatin-based adjuvant chemotherapy. A high-throughput RNAi screening targeting 626 human kinase genes was performed to identify kinase genes whose inhibition potentiates oxaliplatin sensitivity in CRC cells. The associations between copy numbers of the candidate genes and recurrence-free survival and overall survival were analyzed in 142 stage III CRC patients receiving first-line oxaliplatin-based adjuvant chemotherapy who were enrolled from two independent hospitals. HT-RNAi screening identified 40 kinase genes whose inhibition potentiated oxaliplatin cytotoxicity in DLD1 cells. The relative copy number (RCN) of MAP4K1 and CDKL4 were associated with increased risks of both recurrence and death. Moreover, significant genes-based risk score and the ratios of RCN of different genes can further categorize patients into subgroups with distinctly differing outcomes. The estimated AUC for the prediction models including clinical variables plus kinase biomarkers was 0.77 for the recurrence and 0.82 for the survival models. The copy numbers of MAP4K1 and CDKL4 can predict clinical outcomes in CRC patients treated with oxaliplatin-based chemotherapy.
| S-EPMC4599307 | biostudies-literature