A PDX model combined with CD-DST assay to evaluate the antitumor properties of KRpep-2d and oxaliplatin in KRAS (G12D) mutant colorectal cancer.
Heliyon
; 8(12): e12518, 2022 Dec.
Article
em En
| MEDLINE
| ID: mdl-36590511
ABSTRACT
Patient-derived xenograft (PDX) models are more faithful in maintaining the characteristics of human tumors than cell lines and are widely used in drug development, although they have some disadvantages, including their relative low success rate, long turn-around time, and high costs. The collagen gel droplet embedded culture drug sensitivity test (CD-DST) has been used as an in-vitro drug sensitivity test for patients with cancer because of its high success rate of primary cell culture, high sensitivity, and good clinical relevance, but it is based on an in-vitro cell culture and may not simulate the tumor microenvironment accurately. This study aims to combine a PDX model with CD-DST to evaluate the efficiency of antitumor agents. KRpep-2d, a small peptide targeting KRAS (G12D), and oxaliplatin were used to verify the feasibility of this approach. Whole-exome sequencing and Sanger sequencing were first applied to test and validate the KRAS mutation status of a panel of colorectal cancer PDX tissues. One PDX model was verified to carry KRAS (G12D) mutation and was used for in-vivo and the CD-DST drug tests. We then established the PDX mouse model from the patient with the KRAS (G12D) mutation and obtained viable cancer cells derived from the same PDX model. Next, the antitumor abilities of KRpep-2d and oxaliplatin were estimated in the PDX model and the CD-DST. We found that KRpep-2d showed no significant antitumor effect on the xenograft model or on cancer cells derived from the same PDX model. In contrast, oxaliplatin showed significant inhibitory effects in both tests. In conclusion, the PDX model in combination with the CD-DST assay is a comprehensive and feasible method of evaluating the antitumor properties of compounds and could be applied for new drug discovery.
Texto completo:
1
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article