Thesis presented October 07, 2024
Abstract:
Cancer is one of the leading causes of death, with an estimated 10 million deaths worldwide by 2022. Kidney cancer accounts for over 400,000 cases each year, and 150,000 deaths. Drug treatments for metastatic renal cell carcinoma have evolved considerably over the last twenty years, with a growing number of targeted therapies based on protein kinase inhibitors and immunotherapies. Despite this, a majority of patients experience a recurrence of kidney cancer after treatment, associated with significant adverse effects. In this context, one of the main challenges of precision medicine is to optimize treatment choice by combining clinical, histological and genomic information about the patient and the tumor. At the same time, molecular profiling technologies (next-generation sequencing, LC-MS/MS) have enabled multi-omics characterization of large cohorts of clear cell renal cell carcinoma (ccRCC) tissues, the majority histological subtype of renal tumor. In my thesis work, the tumor microenvironment (TME) and DNA methylation of ccRCC were studied to reveal causes and markers of response to anti-tumor treatments.
In a first study, we identified three TME subtypes distinguished by their richness in T-CD8 immune cells and plasma cells, as well as by the expression of immunoglobulin genes. We then showed that a score reflecting the differential between tumor and immune cells (TID) and expression of the associated YWHAE gene outperformed previously published methods in predicting response to immunotherapy.
In a second study, we showed that ccRCC DNA methylation subtypes were associated with differences in response to protein kinase inhibitors (TKIs) and immunotherapy. A model for predicting ccRCC DNA methylation subtypes was developed based on the expression ratios of two genes (IGF2BP3/PCCA, TNNT1/TMEM88). This model provides cost-effective molecular information for treatment selection without methylation data. These results contribute to a finer individual characterization of the cellular and molecular aspects of ccRCCs for the selection of the appropriate treatment for each patient.
Keywords:
Tumor microenvironment, cancer , biomarkers, immunotherapy , kidney, epigenetics, omics, pharmacogenomics, treatment response