ArticleCancers2024
A Retrospective View of the Triple-Negative Breast Cancer Microenvironment: Novel Markers, Interactions, and Mechanisms of Tumor-Associated Components Using Public Single-Cell RNA-Seq Datasets.
Article in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed, 4 citations in OpenAlex.
- Review
- Predictive value of tumoral and peritumoral radiomic features in neoadjuvant chemotherapy response for breast cancer: a retrospective study.La Radiologia medica · 2025Article
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 at 2 institutions in 1 country.
Funding
Abstract
Triple-negative breast cancer (TNBC) is a significant clinical challenge due to its aggressive nature and limited treatment options. In search of new treatment targets, not only single genes but also gene pairs involved in protein interactions, we explored the tumor microenvironment (TME) of TNBC from a retrospective point of view, using public single-cell RNA sequencing datasets. A High-resolution Cell type Annotation Tool, HiCAT, was used first to identify the cell type in 3-level taxonomies. Tumor cells were then identified based on the estimates of copy number variation. With the annotation results, differentially expressed genes were analyzed to find subtype-specific markers for each cell type, including tumor cells, fibroblast, and macrophage. Cell-cell interactions were also inferred for each cell type pair. Through integrative analysis, we could find unique TNBC markers not only for tumor cells but also for various TME components, including fibroblasts and macrophages. Specifically, twelve marker genes, including
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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.