ArticleSTAR protocols2024
Protocol for studying macrophage lipid crosstalk with murine tumor cells.
Article in STAR protocols, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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
1 citing paper in PubMed.
- The janus-faced biology of GPNMB: from tissue homeostasis to cancer pathogenesis.Frontiers in molecular biosciences · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lipid accumulation has recently emerged as a key feature underlying the pro-tumorigenic role of macrophages. Here, we present a workflow to study macrophage lipid crosstalk with tumor cells. We describe steps for the identification, purification, and multi-omics characterization of lipid-laden macrophages (LLMs) from murine tumors and outline protocols to assess the functional significance of LLMs in cancer malignancy. This approach has the potential to uncover the source of lipids that drives LLM formation and its pro-tumorigenic potential in multiple cancer types. For complete details on the use and execution of this protocol, please refer to Kloosterman, Erbani, et al.
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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.