Evidence map›Paper›PMID 33632339›Full record

ArticleLaboratory animal research2021

Sex-dependent liver cancer xenograft models for predicting clinical data in the evaluation of anticancer drugs.

Sungryong Oh, Joohee Jung

Open access · diamondAbstract read
In one paragraph

Article in Laboratory animal research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 22% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
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  3. Article
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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.

Sungryong OhCollege of Pharmacy, Duksung Women's University, #33, Samyang-ro 144-gil, Dobong-gu, Seoul, 01369, South Korea.
Joohee JungCollege of Pharmacy, Duksung Women's University, #33, Samyang-ro 144-gil, Dobong-gu, Seoul, 01369, South Korea. joohee@duksung.ac.kr.ORCID http://orcid.org/0000-0001-9124-9052
Duksung Women's University · KR

Funding

Duksung Women's University Research Grants 3000003365
6 · The paper itself

Abstract

backgroundThe incidence and mortality of liver cancer show a great difference between the sexes. We established sex-dependent liver cancer xenograft models and investigated whether such sex-dependent models could be used to simultaneously evaluate the therapeutic and adverse effects of anticancer drugs for drug screening.

resultsIn the in-vitro test, the cytotoxicity of anticancer drugs (cisplatin, 5-fluorouracil, and doxorubicin) was compared between male- and female-derived liver cancer cell lines. Cisplatin and 5-fluorouracil exhibited cytotoxicity without sex-difference, but doxorubicin showed dose-dependently significant cytotoxicity only in male-derived cells. Our results showed a strong correlation between preclinical and clinical data with the use of sex-dependent liver cancer xenograft models. Moreover, the male-derived Hep3B-derived xenograft model was more sensitive than the female-derived SNU-387-derived xenograft model against doxorubicin treatment. Doxorubicin showed more severe cardiotoxicity in the male xenograft model than in the female model. We investigated the occurrence frequency of doxorubicin-related cardiotoxicity using data obtained from the Korea Institute of Drug Safety & Risk Management Database, but no significant difference was observed between the sexes.

conclusionsOur results suggest that sex-dependent xenograft models are useful tools for evaluating the therapeutic and adverse effects of anticancer drugs, because sex is an important consideration in drug development.

Indexed as

CardiotoxicityDoxorubicinLiver cancerSex differenceThe Korea Institute of Drug Safety & risk management databaseXenograft model

Identifiers

PMID33632339
PMCPMC7905914
OpenAlexW3131344844

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.