Precise Therapy for mCRPC Patients Through Whole Exome Sequencing(PTtWES)

Overview

Through gene sequencing of the patient's tissue, to figure out the genomic characteristics of patients with advanced disease and guide the treatment of patients

Tumor heterogeneity and tumor clonal evolution cause he diagnosis and treatment difficulties of advanced prostate cancer. Heterogeneity exists in different lesions at the same location of the same tumor, between lesions at different locations, and in the same lesion in different processes of disease progression. Tumor heterogeneity causes different tumor patients to respond differently to different treatments; as patients progress, tumor patients gradually develop clonal evolution, and the original effective treatment will lose the therapeutic effect. And routine imaging examinations and PSA examinations are also difficult to respond to changes in the patient's condition in a timely manner. By Genetic testing of the primary tumor, metastases or blood of the patient, and according to the test result of the patient, the patient's medication treatment can be provided, and the patient's condition change can be monitored. Studies have shown that patients with different mutation types respond differently to the same treatment. Prostate cancer patients with AR-V7 mutations have a poorer response to abiraterone or dextrozamide than patients with prostate cancer without AR-V7 mutation; whereas for solid tumors with MSI-H or dMMR, PD-1 Inhibitors can also bring the desired results to such patients. Therefore, according to the genetic test results of the patient's tumor tissue, early diagnosis can also be given, and the patient's condition change and precise treatment can be predicted.In this study, the investigators hope to obtain the genome characteristics of advanced patients by performing whole exon sequencing on the patient's tissues, and to guide the patients' follow-up treatment through sequencing results, to observe the effects of different treatment methods on patients and find biomarker that predict patient prognosis

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