ReviewEJNMMI research2022
Promise and challenges of clinical non-invasive T-cell tracking in the era of cancer immunotherapy.
Review in EJNMMI research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 14 citations in OpenAlex.
- Positron Emission Tomography Imaging of the Adaptive Immune System in Cardiovascular Diseases.Chemical & biomedical imaging · 2025Review
- Recent advances in non-invasiveBiomaterials science · 2025Review
- Ultra-low dose immunoPET usingFrontiers in medicine · 2025Article
- CAR T cells: engineered immune cells to treat brain cancers and beyond.Molecular cancer · 2023Review
- Modeling and affinity maturation of an anti-CD20 nanobody: a comprehensive in-silico investigation.Scientific reports · 2023Article
- Insights into the tumor microenvironment of B cell lymphoma.Journal of experimental & clinical cancer research : CR · 2022Review
- Recent Advances in Exosomal miRNA Biosensing for Liquid Biopsy.Molecules (Basel, Switzerland) · 2022Review
- Radionuclide Imaging of Cytotoxic Immune Cell Responses to Anti-Cancer Immunotherapy.Biomedicines · 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
6 authors at 2 institutions in 1 country.
Funding
Abstract
In the last decades, our understanding of the role of the immune system in cancer has significantly improved and led to the discovery of new immunotherapeutic targets and tools, which boosted the advances in cancer immunotherapy to fight a growing number of malignancies. Approved immunotherapeutic approaches are currently mainly based on immune checkpoint inhibitors, antibody-derived targeted therapies, or cell-based immunotherapies. In essence, these therapies induce or enhance the infiltration and function of tumor-reactive T cells within the tumors, ideally resulting in complete tumor eradication. While the clinical application of immunotherapies has shown great promise, these therapies are often accompanied either by a variety of side effects as well as partial or complete unresponsiveness of a number of patients. Since different stages of disease progression elicit different local and systemic immune responses, the ability to longitudinally interrogate the migration and expansion of immune cells, especially T cells, throughout the whole body might greatly facilitate disease characterization and understanding. Furthermore, it can serve as a tool to guide development as well as selection of appropriate treatment regiments. This review provides an overview about a variety of immune-imaging tools available to characterize and study T-cell responses induced by anti-cancer immunotherapy. Moreover, challenges are discussed that must be taken into account and overcome to use immune-imaging tools as predictive and surrogate markers to enhance assessment and successful application of immunotherapies.
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.