ReviewMetabolites2020
Resolving Metabolic Heterogeneity in Experimental Models of the Tumor Microenvironment from a Stable Isotope Resolved Metabolomics Perspective.
Review in Metabolites, 2020. 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.
- Phospholipid-Rich DC-Vesicles with Preserved Immune Fingerprints: A Stable and Scalable Platform for Precision Immunotherapy.Biomedicines · 2025Article
- Patient-derived organotypic tissue cultures as a platform to evaluate metabolic reprogramming in breast cancer patients.The Journal of biological chemistry · 2025Article
- Challenges of Spatially Resolved Metabolism in Cancer Research.Metabolites · 2024Review
- Stable Isotope Tracing Analysis in Cancer Research: Advancements and Challenges in Identifying Dysregulated Cancer Metabolism and Treatment Strategies.Metabolites · 2024Review
- Single cell metabolism: current and future trends.Metabolomics : Official journal of the Metabolomic Society · 2022Review
- NMR and Metabolomics-A Roadmap for the Future.Metabolites · 2022Review
- Clinical Application Perspectives of Lung Cancers 3D Tumor Microenvironment Models for In Vitro Cultures.International journal of molecular sciences · 2022Review
- Challenges and Opportunities for Immunoprofiling Using a Spatial High-Plex Technology: The NanoString GeoMxFrontiers in oncology · 2022Review
- Innate immune activation by checkpoint inhibition in human patient-derived lung cancer tissues.eLife · 2021Article
- Review
- Multiphoton Microscopy and Mass Spectrometry for Revealing Metabolic Heterogeneity of HepatocytesSovremennye tekhnologii v meditsine · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
The tumor microenvironment (TME) comprises complex interactions of multiple cell types that determines cell behavior and metabolism such as nutrient competition and immune suppression. We discuss the various types of heterogeneity that exist in solid tumors, and the complications this invokes for studies of TME. As human subjects and in vivo model systems are complex and difficult to manipulate, simpler 3D model systems that are compatible with flexible experimental control are necessary for studying metabolic regulation in TME. Stable Isotope Resolved Metabolomics (SIRM) is a valuable tool for tracing metabolic networks in complex systems, but at present does not directly address heterogeneous metabolism at the individual cell level. We compare the advantages and disadvantages of different model systems for SIRM experiments, with a focus on lung cancer cells, their interactions with macrophages and T cells, and their response to modulators in the immune microenvironment. We describe the experimental set up, illustrate results from 3D cultures and co-cultures of lung cancer cells with human macrophages, and outline strategies to address the heterogeneous TME.
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.