Evidence map›Paper›PMID 35631632›Full record

ArticlePharmaceutics2022

Chitooligosaccharides Improve the Efficacy of Checkpoint Inhibitors in a Mouse Model of Lung Cancer.

Astrid Zedlitz Johansen, Marco Carretta, Marie-Louise Thorseth, Shawez Khan, Klaire Yixin Fjæstad, Christian Beltoft Brøchner, Hannes Linder, Christina Ankjærgaard, Marco Donia, Inna Chen and 3 more

Open access · goldAbstract read
In one paragraph

Article in Pharmaceutics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.8field-weighted citation impact, top 31% 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

7 citing papers in PubMed, 9 citations in OpenAlex.

  1. Trial
  2. Review
  3. Review
  4. Article
  5. Review
  6. Review
  7. 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

13 authors at 4 institutions in 1 country.

Astrid Zedlitz JohansenNational Center for Cancer Immune Therapy, Department of Oncology, Copenhagen University Hospital-Herlev and Gentofte, 2730 Herlev, Denmark.ORCID 0000-0002-4948-6799
Marco CarrettaNational Center for Cancer Immune Therapy, Department of Oncology, Copenhagen University Hospital-Herlev and Gentofte, 2730 Herlev, Denmark.
Marie-Louise ThorsethNational Center for Cancer Immune Therapy, Department of Oncology, Copenhagen University Hospital-Herlev and Gentofte, 2730 Herlev, Denmark.ORCID 0000-0001-7978-5549
Shawez KhanNational Center for Cancer Immune Therapy, Department of Oncology, Copenhagen University Hospital-Herlev and Gentofte, 2730 Herlev, Denmark.
Klaire Yixin FjæstadNational Center for Cancer Immune Therapy, Department of Oncology, Copenhagen University Hospital-Herlev and Gentofte, 2730 Herlev, Denmark.
Christian Beltoft BrøchnerDepartment of Pathology, Centre of Diagnostic Investigations, Copenhagen University Hospital-Rigshospitalet, 2100 Copenhagen, Denmark.ORCID 0000-0001-6838-6729
Hannes LinderNational Center for Cancer Immune Therapy, Department of Oncology, Copenhagen University Hospital-Herlev and Gentofte, 2730 Herlev, Denmark.
Christina AnkjærgaardDepartment of Health Technology, Technical University of Denmark, 4000 Roskilde, Denmark.ORCID 0000-0001-5620-6663
Marco DoniaNational Center for Cancer Immune Therapy, Department of Oncology, Copenhagen University Hospital-Herlev and Gentofte, 2730 Herlev, Denmark.ORCID 0000-0003-4966-9752
Inna ChenDepartment of Oncology, Copenhagen University Hospital-Herlev and Gentofte, 2730 Herlev, Denmark.ORCID 0000-0003-2891-0762
Dorte Lisbet NielsenDepartment of Oncology, Copenhagen University Hospital-Herlev and Gentofte, 2730 Herlev, Denmark.
Claus Preibisch BehrensDepartment of Health Technology, Technical University of Denmark, 4000 Roskilde, Denmark.
Daniel Hargbøl MadsenNational Center for Cancer Immune Therapy, Department of Oncology, Copenhagen University Hospital-Herlev and Gentofte, 2730 Herlev, Denmark.
Gentofte Hospital · DKCopenhagen University Hospital · DKUniversity of Copenhagen · DKTechnical University of Denmark · DK

Funding

BrainLab no grant numberDanish Cancer Society R174-A11581-17-S52Lundbeck Foundation R307-2018-3326Varian no grant numberViewRay no grant number
6 · The paper itself

Abstract

YKL-40 (also named chitinase 3 like-1 protein [CHI3L1]) is a secreted chitinase-like protein which is upregulated in cancers and suggested to have pro-tumorigenic activity. YKL-40 lacks enzymatic function, but it can bind carbohydrates such as chitin. Chitooligosaccharides (COS) derived from deacetylation and hydrolysis of chitin might be used for the blockade of YKL-40 function. Here, public single-cell RNA sequencing datasets were used to elucidate the cellular source of YKL-40 gene expression in human tumors. Fibroblasts and myeloid cells were the primary sources of YKL-40. Screening of YKL-40 gene expression in syngeneic mouse cancer models showed the highest expression in the Lewis lung carcinoma (LL2) model. LL2 was used to investigate COS monotherapy and combinations with immune checkpoint inhibitors (anti-PD-L1 and anti-CTLA-4) (ICIs) and radiotherapy (8 Gy × 3) (RT). COS tended to reduce plasma YKL-40 levels, but it did not affect tumor growth. LL2 showed minimal responses to ICIs, or to RT alone. Interestingly, ICIs combined with COS led to delayed tumor growth. RT also enhanced the efficacy of ICIs; however, the addition of COS did not further delay the tumor growth. COS may exert their anti-tumorigenic effects through the inhibition of YKL-40, but additional functions of COS should be investigated.

Indexed as

checkpoint inhibitorschitinchitooligosaccharidesimmunotherapylung cancerradiotherapysyngeneic mouse cancer modelsYKL-40

Identifiers

PMID35631632
PMCPMC9147765
OpenAlexW4280626413

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.