Evidence map›Paper›PMID 32878065›Full record

ArticlePharmaceutics2020

A Tumor-Immune Interaction Model for Synergistic Combinations of Anti PD-L1 and Ionizing Irradiation Treatment.

Jong Hyuk Byun, In-Soo Yoon, Yong Dam Jeong, Sungchan Kim, Il Hyo Jung

Abstract read
In one paragraph

Article in Pharmaceutics, 2020. 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
–field-weighted citation impact
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.

  1. Review
  2. Review
  3. AnJournal of the Royal Society, Interface · 2023
    Article
  4. Review
  5. Novel Anticancer Strategies.Pharmaceutics · 2021
    Article
  6. Review
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

5 authors.

Jong Hyuk ByunDepartment of Mathematics, Pusan National University, Busan 46241, Korea.ORCID 0000-0001-6334-8176
In-Soo YoonCollege of Pharmacy, Pusan National University, Busan 46241, Korea.ORCID 0000-0002-0997-5723
Yong Dam JeongDepartment of Mathematics, Pusan National University, Busan 46241, Korea.ORCID 0000-0002-3970-7690
Sungchan KimDepartment of Mathematics, Pusan National University, Busan 46241, Korea.
Il Hyo JungDepartment of Mathematics, Pusan National University, Busan 46241, Korea.

Funding

National Research Foundation of Korea NRF-2018H1A2A1062811National Research Foundation of Korea NRF-2019R1A2C2007249National Research Foundation of Korea NRF-2020R1C1C1A01004631
6 · The paper itself

Abstract

Combination therapy with immune checkpoint blockade and ionizing irradiation therapy (IR) generates a synergistic effect to inhibit tumor growth better than either therapy does alone. We modeled the tumor-immune interactions occurring during combined IT and IR based on the published data from Deng et al. The mathematical model considered programmed cell death protein 1 and programmed death ligand 1, to quantify data fitting and global sensitivity of critical parameters. Fitting of data from control, IR and IT samples was conducted to verify the synergistic effect of a combination therapy consisting of IR and IT. Our approach using the model showed that an increase in the expression level of PD-1 and PD-L1 was proportional to tumor growth before therapy, but not after initiating therapy. The high expression level of PD-L1 in T cells may inhibit IT efficacy. After combination therapy begins, the tumor size was also influenced by the ratio of PD-1 to PD-L1. These results highlight that the ratio of PD-1 to PD-L1 in T cells could be considered in combination therapy.

Indexed as

anti-PD-L1global sensitivityimmuno-oncologyimmunotherapyionizing irradiationmathematical modelingpharmacokineticstumor-immune interaction

Identifiers

PMID32878065
PMCPMC7558639

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.