Evidence map›Paper›PMID 34164399›Full record

ArticleFrontiers in cell and developmental biology2021

Prediction of Sensitivity and Efficacy of Clinical Chemotherapy Using Larval Zebrafish Patient-Derived Xenografts of Gastric Cancer.

Jing Zhai, Jiaqi Wu, Yaohui Wang, Ruoyue Fan, Guiping Xie, Fangfang Wu, Yani He, Sitong Qian, Aimin Tan, Xuequan Yao and 2 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cell and developmental biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.9field-weighted citation impact, top 32% 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

11 citing papers in PubMed, 12 citations in OpenAlex.

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  11. A zebrafish colorectal xenograft model for chemotherapy response.Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologie
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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

12 authors at 4 institutions in 1 country.

Jing ZhaiDepartment of Surgical Oncology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Jiaqi WuInstitute of Translational Medicine, College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing, China.
Yaohui WangDepartment of Pathology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Ruoyue FanInstitute of Translational Medicine, College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing, China.
Guiping XieDepartment of Surgical Oncology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Fangfang WuInstitute of Translational Medicine, College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing, China.
Yani HeDepartment of Surgical Oncology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Sitong QianInstitute of Translational Medicine, College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing, China.
Aimin TanNanjing Amory Biotech Co. Ltd., Nanjing, China.
Xuequan YaoDepartment of Surgical Oncology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Mingfang HeInstitute of Translational Medicine, College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing, China.
Lizong ShenDepartment of Surgical Oncology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Nanjing Tech University · CNNanjing University of Chinese Medicine · CNJiangsu Province Hospital · CNViva Biotech (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPerioperative chemotherapy has been accepted as one of the most common approaches for locally advanced gastric cancer. However, the efficacy of chemotherapy varies among patients, and there is no effective method to predict the chemotherapy efficacy currently. We previously established the first larval zebrafish patient-derived xenografts (zPDXs) of gastric cancer as a platform for the translational research and personalized treatment. The objective of this study was to investigate the feasibility of screening individualized chemotherapeutics using the zPDXs.

methodsWe further optimized this zPDXs platform including administration route, drug dosing, and rhythm to develop a stable and reliable protocol for chemotherapeutics screening. Using the novel platform, we investigated the chemosensitivity of 5-fluorouracil, cisplatin, docetaxel, and doxorubicin for gastric cancer patients.

resultsWe showed that the engrafted zebrafish retained the original prominent cell components of the corresponding human tumor tissues, and we successfully obtained the results of chemosensitivity of 5-fluorouracil, cisplatin, docetaxel, and doxorubicin for 28 patients with locally advanced gastric cancer. These patients underwent radical gastrectomy for curative intent and 27 cases received postoperative adjuvant chemotherapy. We revealed that the chemosensitivity obtained from zPDXs was consistent with the clinical responses in these patients (

conclusionOur study with the largest sample size so far suggests that larval zPDXs help to predict the chemotherapeutics response and to achieve precise chemotherapy for gastric cancer.

Indexed as

chemotherapygastric cancerprecision cancer medicinetranslational researchzebrafish patient-derived xenografts

Identifiers

PMID34164399
PMCPMC8215369
OpenAlexW3170607898

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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.