The term “personalized medicine” remains an overused promise to apply specific treatment plans matched to the unique aspects of a patient’s disease.

When stripped of its marketing noise, it implies the ability to measure and manage a patient’s complex risk profile.

In cancers, this means predicting a tumor’s inherent biology. Unfortunately, only crude methods of estimating tumor risk exist as genitourinary biomarkers demonstrate either low sensitivity/specificity (prostate/bladder markers) or are altogether unavailable (kidney biomarkers).  We are therefore left with stage, grade and histology as the most relevant predictors of a tumor’s biology, the limitations of which are well known to clinicians.

A predominant theme at the recent Genitourinary Cancers Symposium was measuring tumor heterogeneity and beginning to manage it clinically—in other words, true “personalized medicine”.  Moving the needle forward are the “omic” sciences (genomics, proteomics, kinomics, metabolomics).

Perhaps nowhere is this better seen than in the case of kidney cancer. For decades, pathologists and clinicians have recognized that renal cell carcinoma (RCC) is not one but several distinct histological/clinical diseases.  With the publication of a kidney cancer molecular atlas, rapid sequencing and increasingly open source data for bioanalysis, a new picture of RCC evolution is emerging.

Investigators from the Royal Marsden Hospital in London have recently sequenced multiple areas in primary RCCs from 10 patients with their corresponding metastases noting that biopsies from the same patient (and even in the same primary) exhibited “unique and private” mutations as often as 65% of the time. Using these data, they developed a model of genetic mutational “branched” evolution in kidney cancer—analogous to a tree with its trunk and many branches.1

They demonstrate that in clear cell RCC, a VHL mutation, is a necessary event (the trunk) but that under unique selective pressures tumor cells can then “privately” evolve along different pathways (the branches) – with some branches overgrowing (metastases) and others thwarted (indolent cancers).  

They postulate that this clonal architecture itself may soon serve as a cancer biomarker (i.e., palm tree phenotypes—long trunk/few branches, perhaps as indolent cancers vs. baobab tree phenotypes—short trunk/many branches, perhaps an aggressive cancer).  This model of “truncal drivers” and “branched evolution” appears to hold up in other cancers as well and has broad clinical implications for tumor risk stratification, drug development, therapeutic decisions, and understanding resistance.

As the kinetics of data acquisition and analysis in the “omic” sciences increases, the moniker “personalized medicine” will be less about market hype and more about clinical hope for both oncologic and benign urologic disease.

  1. Gerlinger et al Nature Genetics (in press)

Robert G. Uzzo, MD, FACS, G. Willing “Wing” Pepper Chair in Cancer Research and Professor and Chairman, Department of Surgery, Fox Chase Cancer Center, Temple University, School of Medicine, Philadelphia.