The molecular epidemiology of Renal cell carcinoma: subtypes and prognosis

Abstract

The field of renal cell carcinoma (RCC) has evolved rapidly over the last five years, with the advent of novel therapies targeting specific molecular pathways dysregulated in RCC. The development of these drugs was via a classic bench-to-bedside fashion, where an understanding of the underlying biology in RCC permitted relevant drug development. The foundation of these biological insights was the careful pathologic subtyping of RCC, supported by advances in familial cancer genetics. These subtypes have tremendous clinical and biologic relevance, further illustrated by the clinical observation that survival outcomes in RCC may diverge more dramatically than almost any other cancer.

The work presented here is divided into two areas ¿ the first being the evaluation of existing clinical models for outcome predictions in RCC, and the second being the evaluation of molecular models in RCC, and corresponding molecular insights. For the first area, we focused on the clinical models where epidemiologists and clinicians are actively seeking an optimal combination of clinico-pathologic variables for subtyping patients with RCC and predicting survival outcomes. Indeed, the literature is replete with a variety of proposed pre-operative and post-operative models. However, much less work has been invested in comparing these multiple models to choose one that is performing optimally. The work presented here compares multiple algorithms and nomograms to select an optimal and practical predictor in localized RCC that may be recommended for use internationally for individual prognostication and in clinical trials of adjuvant therapy. We compare several clinical post-operative models including the Leibovich model, the UCLA Integrated Staging System (UISS), the Karakiewicz nomogram, the Kattan nomogram and the Sorbellini nomogram, and conclude that the best performing model is the Karakiewicz nomogram. This finding is of relevance in individual patient counseling, biomarker research and pharmaceutical trial design for adjuvant therapy.

For the second area on molecular models in RCC, I derive and evaluate useful molecular predictors in the various subtypes of RCC in terms of pathology and prognosis. Thus, various hitherto undescribed subtypes of RCC with distinct molecular and clinical profiles may be defined here. We have generated novel expression predictors of prognosis in clear cell RCC as well as papillary RCC, while concurrently generating insights into the molecular mechanisms underpinning these prognostic differences. For the rarer chromophobe RCC, we have reported a novel expression predictor discriminating chromophobe RCC from its close benign counterpart, renal oncocytoma, which was externally validated. We also found that somatic pairing of chromosome 19q, an unusual cytogenetic finding, was found in renal oncocytoma but not in chromophobe RCC, and was associated with deregulated oxygen-sensing response. Overall, our findings provide not only a comprehensive analysis of gene expression in the various molecular subtypes of RCC, but has also provided multiple insights into the potential pathogenesis of each RCC subtype.

Finally, I hope that this work embodied in this thesis allows the scientific community investigating RCC to prepare its labours with a firm foundation from a clear understanding of the molecular epidemiology and pathology of RCC.