AUA 2018: Debate: 10 years of Big Data Have Changed Renal Cell Carcinoma Management

San Francisco, CA USA ( In this lively last debate, the focus was on whether big data has changed RCC management. Dr. Shuch focused recent findings that have affected our understanding of renal cell carcinoma (RCC). He emphasized that “Big Data” is not large population-level databases, but rather next-generation sequencing; data on the order megabases and kilobases. There have many articles using different datasets, both public and institutional, that have explored RCC genomic profiles in an effort to answer bigger questions.

The three main uses for big data in RCC have been molecular subtyping, prognostication, and therapeutic targeting. 

Molecular subtyping:
First, genomic classification of RCC can overcome the subjectivity and interobserver variability of traditional pathology (even in the hands of excellent GU pathologists). Similarly, in the nebulous space of “oncocytic neoplasm, cannot rule out oncocytoma,” use of copy number variation may be useful to more definitively tell a patient they have a benign tumor. In 2018, approximately 4% of RCC’s remain unclassified – which he finds unacceptable; genomic classifiers may help negative this condition.

There are now multiple I/O adjuvant trials ongoing and one approved agent for adjuvant therapy (sunitinib). No FDA approved biomarkers for patient selection.  Yet, the CCP (Myriad) tool is tissue agnostic – and can be ordered today (but not reimbursed). Multiple studies have demonstrated its ability to predict patients with worse RFS and DFS.

Therapeutic Selection:
There are many agents now available in 2018 for patients with metastatic RCC. There are also well-defined mutations in RCC and its subtypes – and unfortunately, most are not targetable or druggable. These mutations may be prognostic and possibly predictive. There are planned prospective biomarker driven trials in clear cell RCC and one active one in papillary RCC.

PDRM1 is one such predictor. It has been found to be predictive of I/O response. Similarly, mTOR/PI3K/AKT/TSC1/TSC2 mutations are found in about 10% of ccRCC patients and can be used to select for levantinib/everolimus combination therapy. MET mutations have been found to be important predictors of response in papillary RCC (JCO 2017).

As costs decrease, these will become standard of care.

Dr. Karam argued the con – specifically that Dr. Shuch showed 10 year’s worth of big data – but none of them have changed management yet. He also believes they will change management in the near future, but they have not impacted day-to-day management yet.

He went on to review all the major guidelines, including ones just published, and none advocate for the use of biomarkers in prime time – as they are not yet validated and ready for clinical use.

So, while the data looks great, it is still expense (he showed an example of a patient that paid $10,000 out of pocket) and not ready for widespread use.

Presented by: Brian Shuch, Yale (PRO) | Jose Karam, MD Anderson (CON)

Written by: Thenappan Chandrasekar, MD, Clinical Fellow, University of Toronto, Twitter: @tchandra_uromd at the 2018 AUA Annual Meeting - May 18 - 21, 2018 – San Francisco, CA USA

Read the First Debate: Active Surveillance for Large Renal Masses is Appropriate

Read the Second Debate: Tumor Enucleation for Sporadic T1 RCC is Oncologically Sound

Read the Third Debate: Adjuvant Therapy for High Risk RCC Should Be Used