From massive parallel sequencing to personalized medicine: comprehensive profiling of structural variants in pharmacogenes and identification of risk and treatment response markers in metastatic renal cancer
Author
Santos Romero, MaríaEntity
UAM. Departamento de Bioquímica; Centro Nacional de Investigaciones Oncológicas (CNIO)Date
2021-12-17Funded by
The following grants have supported the research presented in this Doctoral Thesis: Proyecto “Europa Excelencia” SAF2015-70820-ERC de la Agencia Estatal de Investigación- Ministerio de Ciencia e Innovación (AEI-MICINN). Proyecto Retos Investigación RTI2018-095039-B-I00 de la Agencia Estatal de Investigación- Ministerio de Ciencia, Innovación y Universidades (AEI-MCIU)Subjects
Biologías Moleculares; Biología y Biomedicina / BiologíaNote
Tesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Medicina, Departamento de Bioquímica. Fecha de Lectura: 17-12-2021Esta tesis tiene embargado el acceso al texto completo hasta el 17-06-2023
Esta obra está bajo una licencia de Creative Commons Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional.
Abstract
Next-generation sequencing (NGS) technologies have enabled the characterization of thousands of genomes in physiological and pathological conditions providing with valuable information for custom-made management of patients. Main clinical challenges such as pharmacotherapy inefficacy and derived toxicities may be preventable by means of genomic-guided drug selection. In the field of oncologic medicine, germline and tumor genetic profile may have high clinical impact for cancer risk prediction, diagnosis, prognosis and therapy. Despite its potential, the application of massive sequencing in the field of medicine is taking its first steps the widespread use of this technology in the daily clinical practice may be the key to take the big leap towards NGS-based personalized medicine.
In this Thesis the main goal was to leverage the power of NGS technologies by studying a broad range of current clinical challenges for health improvement. Specific aims were to identify novel structural variants in pharmacogenes that may have a relevant contribution for pharmacotherapy outcome, and to identify genetic markers of risk and treatment response in patients with metastatic renal cell carcinoma (RCC).
First, we integrated whole genome and exome sequencing data from thousands of individuals compiled in extensive genomic databases to comprehensively characterize novel copy-number variants across 208 clinically relevant pharmacogenes. Through this approach, we found out that novel deletions are highly population-specific and have a significant contribution to the total burden of loss-of-function alleles in pharmacogenes. These findings pointed out the importance of comprehensive NGS-based genotype characterization of pharmacogenes for an accurate prediction of drug response.
Second, we assessed the prevalence of germline mutations in patients with metastatic RCC by sequencing 29 cancer susceptibility genes in 294 unselected metastatic RCC cases, plus 21 patients with clinical RCC-hereditary features. As result, we observed a higher prevalence of germline mutations in RCC-related genes in patients with non-clear cell histology. Even more, 40% of papillary type 2 tumors were FH-carriers, highlighting that patients with this histological subtype would benefit from FH genetic testing.
Third, we performed a molecular and immunohistochemical characterization of mTOR pathway components in a series of 105 RCC patients treated with mTOR inhibitors, in order to identify molecular markers of treatment response. In this study we found that mTOR pathway mutations, a negative staining of PTEN immunohistochemistry (IHC) and their combination are potential markers predictive of rapalog response.
Finally, we determined how individual and concurrent mutations in the chromatin remodelers PBRM1 and KDM5C impacted tumor angiogenesis and the response to antiangiogenic treatment in a series of 155 metastatic RCC patients treated with first-line antiangiogenic therapy. As result we found that concurrent mutations in PBRM1 and KDM5C are common in clear cell RCC patients and likely cooperate to increase the sensitivity to antiangiogenic monotherapy
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