ArticleNeoplasia (New York, N.Y.)2019
Cellular Metabolic Heterogeneity In Vivo Is Recapitulated in Tumor Organoids.
Article in Neoplasia (New York, N.Y.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 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
51 citing papers in PubMed, 74 citations in OpenAlex.
- Article
- Organoids glimpse: the nexus for diverse tumor heterogeneity.Frontiers in cell and developmental biology · 2026Review
- Delineation of gastrointestinal tumors biopsies using a fluorescence lifetime imaging optical fiber probe.Journal of biophotonics · 2025Article
- Fluorescence Lifetime Imaging Techniques-A Review on Principles, Applications and Clinical Relevance.Journal of biophotonics · 2025Review
- Wide-Field Optical Redox Imaging with Leading-Edge Detection Enables Assessment of Treatment Response and Heterogeneity in Patient-Derived Cancer Organoids.Cancer research · 2025Article
- Resistance to neoadjuvant chemotherapy in breast cancers: a metabolic perspective.Journal of experimental & clinical cancer research : CR · 2025Review
- Subclonal response heterogeneity to define cancer organoid therapeutic sensitivity.Scientific reports · 2025Article
- A New Perspective on Precision Medicine: The Power of Digital Organoids.Biomaterials research · 2025Review
- Review
- The Use of Patient-Derived Organoids in the Study of Molecular Metabolic Adaptation in Breast Cancer.International journal of molecular sciences · 2024Review
- Evaluation of Cellpose segmentation with sequential thresholding for instance segmentation of cytoplasms within autofluorescence images.Computers in biology and medicine · 2024Article
- Insights into metabolic heterogeneity of colorectal cancer gained from fluorescence lifetime imaging.eLife · 2024Article
- Imaging immunometabolismImmunometabolism (Cobham, Surrey) · 2024Article
- Optical imaging reveals chemotherapy-induced metabolic reprogramming of residual disease and recurrence.Science advances · 2024Article
- Single cell metabolic imaging of tumor and immune cellsFrontiers in oncology · 2023Article
- Fabrication of lumen-forming colorectal cancer organoids using a newly designed laminin-derived bioink.International journal of bioprinting · 2023Article
- Tumor heterogeneity: preclinical models, emerging technologies, and future applications.Frontiers in oncology · 2023Review
- POSEA: A novel algorithm to evaluate the performance of multi-object instance image segmentation.PloS one · 2023Article
- Label-free metabolic imaging for sensitive and robust monitoring of anti-CD47 immunotherapy response in triple-negative breast cancer.Journal for immunotherapy of cancer · 2022Article
- Technologies to Assess Drug Response and Heterogeneity in Patient-Derived Cancer Organoids.Annual review of biomedical engineering · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 5 institutions in 1 country.
Funding
Abstract
Heterogeneous populations within a tumor have varying metabolic profiles, which can muddle the interpretation of bulk tumor imaging studies of treatment response. Although methods to study tumor metabolism at the cellular level are emerging, these methods provide a single time point "snapshot" of tumor metabolism and require a significant time and animal burden while failing to capture the longitudinal metabolic response of a single tumor to treatment. Here, we investigated a novel method for longitudinal, single-cell tracking of metabolism across heterogeneous tumor cell populations using optical metabolic imaging (OMI), which measures autofluorescence of metabolic coenzymes as a report of metabolic activity. We also investigated whether in vivo cellular metabolic heterogeneity can be accurately captured using tumor-derived three-dimensional organoids in a genetically engineered mouse model of breast cancer. OMI measurements of response to paclitaxel and the phosphatidylinositol-3-kinase inhibitor XL147 in tumors and organoids taken at single cell resolution revealed parallel shifts in metaboltruic heterogeneity. Interestingly, these previously unappreciated heterogeneous metabolic responses in tumors and organoids could not be attributed to tumor cell fate or varying leukocyte content within the microenvironment, suggesting that heightened metabolic heterogeneity upon treatment is largely due to heterogeneous metabolic shifts within tumor cells. Together, these studies show that OMI revealed remarkable heterogeneity in response to treatment, which could provide a novel approach to predict the presence of potentially unresponsive tumor cell subpopulations lurking within a largely responsive bulk tumor population, which might otherwise be overlooked by traditional measurements.
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.