# Individualized drug screening in cholangiocarcinoma using organoid models and patient-derived tumor xenograft

## TL;DR

This study shows that organoid and xenograft models can help personalize chemotherapy for cholangiocarcinoma patients by predicting drug responses.

## Contribution

The study demonstrates the combined use of PDO and PDX models to guide individualized chemotherapy in cholangiocarcinoma.

## Key findings

- 18 PDO and 21 PDX models were successfully established from CCA patient samples.
- PDO and PDX models retained the mutational profiles of the original tumors.
- Drug sensitivity in models correlated with actual clinical treatment responses.

## Abstract

Cholangiocarcinoma (CCA) is a highly aggressive biliary malignancy with a very poor prognosis. How to screen the optimal chemotherapy regimen is crucial for enhancing the prognosis of CCA patients. The study aims to develop patient-derived tumor organoid (PDO) models and patient-derived tumor xenograft (PDX) models of CCA to simulate clinical responses to chemotherapy.

Tumor tissues were collected from patients undergoing surgical resection and subsequently utilized to establish PDO and PDX models. Hematoxylin-eosin (H&E), immunohistology (IHC), and immunofluorescence (IF) were conducted to analyze the biological characteristics of these PDXs and PDOs. Whole exome sequencing (WES) was performed to identify the mutation types of primary tumor, PDO, and PDX. Drug sensitivity assays were conducted utilizing PDO and PDX models to compare clinical treatment responses.

In this study, we successfully established 18 PDO (success rate, 56.3%) models and 21 PDX models (success rate, 65.6%) from 32 patients diagnosed with CCA. PDO and PDX preserved the mutational profiles characteristic of the primary tumor samples. The drug screening results from PDOs demonstrated a correlation with the actual clinical response to chemotherapy regimens, and these findings were further validated in PDX models.

Our findings indicate that the integration of PDO and PDX models can successfully guide clinical treatment strategies, facilitating effective personalized therapy for CCA patients.

The online version contains supplementary material available at 10.1186/s12885-025-15495-w.