Evidence map›Paper›PMID 34746010›Full record

ReviewFrontiers in oncology2021

Target-Based Radiosensitization Strategies: Concepts and Companion Animal Model Outlook.

Matthew R Berry, Timothy M Fan

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.5field-weighted citation impact, top 17% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 12 citations in OpenAlex.

  1. Peptide-Based Biomaterials as a Promising Tool for Cancer Radiotherapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Matthew R BerryDepartment of Veterinary Clinical Medicine, University of Illinois at Urbana-Champaign, Champaign, IL, United States.
Timothy M FanDepartment of Veterinary Clinical Medicine, University of Illinois at Urbana-Champaign, Champaign, IL, United States.
University of Illinois Urbana-Champaign · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

External beam radiotherapy is indicated in approximately 50-60% of human cancer patients. The prescribed dose of ionizing radiation that can be delivered to a tumor is determined by the sensitivity of the normal surrounding tissues. Despite dose intensification provided by highly conformal radiotherapy, durable locoregional tumor control remains a clinical barrier for recalcitrant tumor histologies, and contributes to cancer morbidity and mortality. Development of target-based radiosensitization strategies that selectively sensitizes tumor tissue to ionizing radiation is expected to improve radiotherapy efficacy. While exploration of radiosensitization strategies has vastly expanded with technological advances permitting the precise and conformal delivery of radiation, maximal clinical benefit derived from radiotherapy will require complementary discoveries that exploit molecularly-based vulnerabilities of tumor cells, as well as the assessment of investigational radiotherapy strategies in animal models that faithfully recapitulate radiobiologic responses of human cancers. To address these requirements, the purpose of this review is to underscore current and emerging concepts of molecularly targeted radiosensitizing strategies and highlight the utility of companion animal models for improving the predictive value of radiotherapy investigations.

Indexed as

comparative oncologyDNA damage responsedog modelmolecular targetsradiotherapy

Identifiers

PMID34746010
PMCPMC8564182
OpenAlexW3205475625

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.