ReviewJournal of personalized medicine2025
Deciphering Breast Tumor Heterogeneity Through Patient-Derived Organoids and Circulating Tumor Cells.
Review in Journal of personalized medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Construction of a novel signature based on CRISPR-Cas9 screening for prognostic prediction in breast cancer.BMC cancer · 2026Article
- Clinical applications and future perspectives of circulating tumor cells in solid tumors.Discover oncology · 2026Review
- MicroRNAs in Breast Cancer: Diagnostic and Prognostic Potential, Challenges, and Clinical Reliability.Biomedicines · 2026Review
- 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
Breast cancer is a highly heterogeneous disease, with tumors capable of adapting to shifting conditions, making the development of effective personalized therapies particularly challenging. Patient-derived models, such as patient-derived organoids (PDOs) and circulating tumor cell (CTC) cultures, have emerged as powerful tools for investigating intra- and inter-tumor heterogeneity. These models largely retain the genetic, phenotypic, and microenvironmental features of the original tumors, providing valuable insights into disease progression, drug response, and resistance mechanisms. Furthermore, by enabling tumors' spatiotemporal molecular profiling, PDOs and CTCs offer a dynamic approach to assess treatment efficacy over time. However, to fully capture the complexity of breast cancer heterogeneity, it is required to develop models from multiple tumor and blood samples collected throughout the course of treatment. This review explores the potential of integrating PDOs and CTC models to better understand intra-tumor heterogeneity while addressing key challenges in developing patient-derived models that accurately recapitulate patients' tumors to advance personalized care. The integration of PDOs and CTCs could represent a paradigm shift in the personalized management of metastatic breast cancer.
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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.