Dataset Information

Presence of Urinary Exosomes for Liquid Biopsy of Clear Cell Renal Cell Carcinoma: Protocol for a Pilot Feasibility Study.

ABSTRACT:

Background

Approximately 70%-80% of kidney cancers are clear cell renal cell carcinomas (CCRCCs). Patient management is based on imaging (abdominal ultrasound and computerized tomography), surgical excision of the tumor, and pathological analysis. A tissue biopsy is therefore necessary to confirm the diagnosis and avoid unnecessary nephrectomy. For metastatic cancers, a tissue biopsy is essential for establishing the targeted therapy. This biopsy of tumor material is invasive and painful. Other techniques such as liquid biopsy would help reduce the need for tissue biopsy. The development of a simple biological test for diagnosis is essential. CA9 is a powerful marker for the diagnosis of CCRCC. Exosomes have become a major source of liquid biopsy because they carry tumor proteins, RNA, and lipids. Urine is the most convenient biological liquid for exosome sampling.

Objective

The aim of this study (PEP-C study) is mainly to determine whether it is possible to detect urinary exosomal CA9 for the molecular diagnosis of CCRCC.

Methods

This study will include 60 patients with CCRCC and 40 noncancer patients. Exosomes will be isolated from urine samples and exosomal CA9 will be detected by transmission electron microscopy, flow cytometry, and reverse transcription-quantitative polymerase chain reaction.

Results

This study is currently underway with funding support from the CHU Saint-Etienne of France.

Conclusions

We expect to demonstrate that urinary tumor exosomes could be a novel liquid biopsy to diagnose CCRCC and to guide clinicians in treatment decision-making.

Trial registration

ClinicalTrials.gov NCT04053855; https://clinicaltrials.gov/ct2/show/NCT04053855.

International registered report identifier (irrid)

DERR1-10.2196/24423.

SUBMITTER: Li G

PROVIDER: S-EPMC8335600 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundParallel development of preclinical models that recapitulate treatment response observed in patients is central to the advancement of personalized medicine.ObjectiveTo evaluate the use of biopsy specimens to develop patient-derived xenografts and the use of corresponding cell lines from renal cell carcinoma (RCC) tumors for the assessment of histopathology, genomics, and treatment response.Design, setting, and participantsA total of 74 tumor specimens from 66 patients with RCC were implanted into immunocompromised NOD-SCID IL2Rg-/- mice. Four cell lines generated from patients' specimens with clear cell pathology were used for comparative studies.Outcome measurements and statistical analysisPreclinical models were established and assessed. Engraftment rates were analyzed using chi-square testing. Analysis of variance (two-way analysis of variance) was conducted to assess tumor growth.Results and limitationsOverall, 33 RCC mouse xenograft models were generated with an overall engraftment rate of 45% (33 of 74). Tumor biopsies engrafted comparably with surgically resected tumors (58% vs 41%; p=0.3). Xenograft tumors and their original tumors showed high fidelity in regard to histology, mutation status, copy number change, and targeted therapy response. Engraftment rates from metastatic tumors were higher but not more significant than primary tumors (54% vs 34%; p=0.091). Our engraftment rate using metastases or biopsies was comparable with recent reports using resected primary tumors. In stark contrast to corresponding cell lines, all tested xenografts recapitulated patients' clinical response to sunitinib.ConclusionsPatient-derived xenograft models can be effectively established from tumor biopsies. Preclinical xenograft models but not matched cell lines reflected clinical responses to sunitinib.Patient summaryMatched patient-derived clear cell renal cell carcinoma xenografts and cell lines from responsive and refractory patients treated with sunitinib were established and evaluated for pharmacologic response to anti-vascular endothelial growth factor treatment. Both models accurately reflected the genetic characteristics of original tumors, but only xenografts recapitulated drug responses observed in patients. These models could serve as a powerful platform for precision medicine.