ReviewProteomics2021
Co-culturing multicellular tumor models: Modeling the tumor microenvironment and analysis techniques.
Review in Proteomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- Micro Pattern-Based 3D Cell Culture Platform: An Overview of Technologies and Applications.Exploration (Beijing, China) · 2026Review
- Breast Cancer Multicellular Spheroid Models-A Tool for Studying Cancer Biology; a Possible Platform for Drug Screening and Personalized Medicine.International journal of molecular sciences · 2026Review
- Article
- Direct transfer of multicellular tumor spheroids grown in agarose microarrays for high-throughput mass spectrometry imaging analysis.Analytical and bioanalytical chemistry · 2025Article
- 3D Hepatocyte Model with Composite Nanofibers That Reproduced Human In Vivo Drug Clearance Profiles.ACS pharmacology & translational science · 2025Article
- Unveiling Therapeutic Opportunities with Melanoma Patient-derived Organoid Models.Journal of visualized experiments : JoVE · 2024Article
- Functional biomaterials for biomimetic 3D in vitro tumor microenvironment modeling.In vitro models · 2023Review
- Towards a New 3Rs Era in the construction of 3D cell culture models simulating tumor microenvironment.Frontiers in oncology · 2023Review
- Three-Dimensional Mass Spectrometry Imaging Reveals Distributions of Lipids and the Drug Metabolite Associated with the Enhanced Growth of Colon Cancer Cell Spheroids Treated with Triclosan.Analytical chemistry · 2022Article
- Lipidomic comparison of 2D and 3D colon cancer cell culture models.Journal of mass spectrometry : JMS · 2022Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Advances in two-dimensional (2D) and three-dimensional (3D) cell culture over the last 10 years have led to the development of a plethora of methods for cultivating tumor models. More recently, cellular co-cultures have become a suitable testbed. The first portion of this review focuses on co-culturing methods that have been developed in recent years utilizing the multicellular tumor spheroid model. The latter portion describes techniques that are used to analyze the proteomes of mono- or co-cultured tumor models, with a focus on mass spectrometry (MS)-based analyses. Protein profiles are important indicators of the tumor heterogeneity. Therefore, there is a specific focus within this review on analysis by MS and MS imaging methods evaluating the proteomic profiles of 2D and 3D co-cultures. While these models are incredibly important for biological research, so far, they have not been widely explored on the proteomic level. With this review, we aim to introduce these systems to an analytical audience, with the goal of highlighting MS as an underutilized tool for proteomic analysis of tumor models.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.