ReviewCancer science2022
Tumor-targeted fluorescence labeling systems for cancer diagnosis and treatment.
Review in Cancer science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 12 citations in OpenAlex.
- Visualization of Immunological Synapse Formation by Intercellular Cross-Linking of T Cell-Dependent Bispecific Antibodies Using Fluorescence Microscopy.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Advances in Natural-Product-Based Fluorescent Agents and Synthetic Analogues for Analytical and Biomedical Applications.Bioengineering (Basel, Switzerland) · 2024Review
- Molecular Insights into the Anticancer Activity of Withaferin-A: The Inhibition of Survivin Signaling.Cancers · 2024Article
- Bacterial imaging in tumour diagnosis.Microbial biotechnology · 2024Review
- Article
- Tumor-targeted fluorescence labeling systems for cancer diagnosis and treatment.Cancer science · 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
9 authors at 4 institutions in 2 countries.
Funding
Abstract
Conventional imaging techniques are available for clinical identification of tumor sites. However, detecting metastatic tumor cells that are spreading from primary tumor sites using conventional imaging techniques remains difficult. In contrast, fluorescence-based labeling systems are useful tools for detecting tumor cells at the single-cell level in cancer research. The ability to detect fluorescent-labeled tumor cells enables investigations of the biodistribution of tumor cells for the diagnosis and treatment of cancer. For example, the presence of fluorescent tumor cells in the peripheral blood of cancer patients is a predictive biomarker for early diagnosis of distant metastasis. The elimination of fluorescent tumor cells without damaging normal tissues is ideal for minimally invasive treatment of cancer. To capture fluorescent tumor cells within normal tissues, however, tumor-specific activated target molecules are needed. This review focuses on recent advances in tumor-targeted fluorescence labeling systems, in which indirect reporter labeling using tumor-specific promoters is applied to fluorescence labeling of tumor cells for the diagnosis and treatment of cancer. Telomerase promoter-dependent fluorescence labeling using replication-competent viral vectors produces fluorescent proteins that can be used to detect and eliminate telomerase-positive tumor cells. Tissue-specific promoter-dependent fluorescence labeling enables identification of specific tumor cells. Vimentin promoter-dependent fluorescence labeling is a useful tool for identifying tumor cells that undergo epithelial-mesenchymal transition (EMT). The evaluation of tumor cells undergoing EMT is important for accurately assessing metastatic potential. Thus, tumor-targeted fluorescence labeling systems represent novel platforms that enable the capture of tumor cells for the diagnosis and treatment of cancer.
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.