ArticlePloS one2021
5-aminolaevulinic acid (5-ALA) accumulates in GIST-T1 cells and photodynamic diagnosis using 5-ALA identifies gastrointestinal stromal tumors (GISTs) in xenograft tumor models.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 13 citations in OpenAlex.
- AnOncology research · 2026Article
- Photodynamic application in diagnostic procedures and treatment of non-melanoma skin cancers.Current treatment options in oncology · 2024Review
- 5-ALA localises to the autophagy compartment and increases its fluorescence upon autophagy enhancement through caloric restriction and spermidine treatment in human glioblastoma.Biochemistry and biophysics reports · 2024Article
- The optimization and application of photodynamic diagnosis and autofluorescence imaging in tumor diagnosis and guided surgery: current status and future prospects.Frontiers in oncology · 2024Review
- A PPIX-binding probe facilitates discovery of PPIX-induced cell death modulation by peroxiredoxin.Communications biology · 2023Article
- Advances in immunology and immunotherapy for mesenchymal gastrointestinal cancers.Molecular cancer · 2023Review
- Fluorescence-Based Microendoscopic Sensing System for Minimally Invasive In Vivo Bladder Cancer Diagnosis.Biosensors · 2022Article
- Advances in Diagnosis and Therapy for Bladder Cancer.Cancers · 2022Review
- Targeted Photodynamic Diagnosis and Therapy for Esophageal Cancer: Potential Role of Functionalized Nanomedicine.Pharmaceutics · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gastrointestinal stromal tumor (GIST) diagnosis using conventional gastrointestinal endoscopy is difficult because such malignancies cannot be distinguished from other types of submucosal tumors. Photodynamic diagnosis (PDD) is based on the preferential uptake of photosensitizers by tumor tissues and its detection by fluorescence emission upon laser excitation. In this study, we investigated whether PDD using 5-aminolevulinic acid (5-ALA), a standard photosensitizer used worldwide, could be used for GIST diagnosis. 5-ALA is metabolized to endogenous fluorescent protoporphyrin IX (PpIX). We examined the accumulation of PpIX in GIST-T1 cells using flow cytometry and immunofluorescent staining. Furthermore, we established GIST-T1 xenograft mouse models and examined PpIX accumulation in the resultant tumors. PpIX accumulated in GIST-T1 cells and was localized mainly to lysosomes. PpIX accumulation was also observed in murine xenograft tumors. Moreover, tumor and normal tissues could be distinctly identified by relative PpIX fluorescence. Thus, our results demonstrated that PDD with 5-ALA has substantial clinical potential for GIST diagnosis.
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.