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Page 2 of 14 Atmaja et al. J Cancer Metastasis Treat 2021;7:xx https://dx.doi.org/10.20517/2394-4722.2021.66

INTRODUCTION
Renal Cell Cancer (RCC) represents 2%-3% of global cancer diagnoses . However, its incidence in the
[1]
[2]
developed world has doubled over the past half-century and is projected to increase . It is the 7th most
common cancer in the UK, with around 13,100 new diagnoses each year . About 30% of patients present
[3]
with metastatic disease at the time of diagnosis and an additional 30% of patients undergoing curative
[4]
surgery for localized RCC, will develop recurrence or metastases .
The systemic treatment for mRCC has evolved substantially over the last decade owing to a better
understanding of the underlying biology of RCC. The discovery of the significance of the vascular
endothelial growth factor (VEGF) and mammalian target of rapamycin (mTOR) pathways has radically
shifted RCC management from interferons in the mid-2000s to novel, targeted agents. More recently,
several immune checkpoint inhibitors (ICIs) have joined the therapeutic options of mRCC. The spectrum of
overall survival in a vastly heterogenous disease such as mRCC ranges from a few months to many years.
Therefore, a risk stratification tool is of paramount importance to guide future individualized treatment
decision-making. In addition, predictive biomarkers are critical for developing personalized care in
oncology; examples include anti-HER2 antibody in HER2-positive breast cancer and BRAF inhibitors in
BRAF mutant melanomas . Unfortunately, no biomarkers currently have equivalent utility in mRCC
[5]
despite the obvious dependence of this disease on the VEGF pathway.

This article will review the treatment landscape of mRCC, evaluate the available risk prognostication tools
and explore potential predictive markers that may help achieve the goal of personalized systemic therapy in
kidney cancer.

PROGNOSTIC CLINICAL MODELS
Appropriate treatment selection in clinical practice is facilitated by prognostic stratification. The era of
VEGF-targeted therapy saw the development of the International mRCC Database Consortium (IMDC), a
clinical model that integrates six variables to stratify patients with mRCC into three prognostic groups
(favorable, intermediate and poor-risk) [Table 1]. It incorporates six prognostic factors that correlate
independently with overall survival (OS): Karnofsky performance status score of less than 80%, an interval
of less than 1 year between diagnosis of RCC and initiation of treatment, corrected serum calcium level
greater than 10mg/dL, hemoglobin levels below the lower limit of normal, high absolute neutrophil and
platelet count. This has largely superseded the Memorial Sloan Kettering Cancer Centre (MSKCC) model,
[6,7]
commonly used in the era of interferon therapy . The median OS associated with each prognostic group is
43 months, 23 months, and 8 months in the favorable, intermediate and poor-risk groups, respectively .
[8]
The IMDC has not only been shown to profile risk using VEGF-targeted agents in the first-line setting, but
also in the second and third-line settings [9,10] . Although the IMDC was specifically applicable to anti-VEGF
therapy, its positive value has also been demonstrated in patients receiving single or combination
immunotherapy [11-13] .

THE USE OF PREDICTIVE BIOMARKERS IN METASTATIC RENAL CELL CARCINOMA
There are various histological subtypes of renal cell carcinoma; the most common of these being clear cell
[14]
RCC (ccRCC), which accounts for over 75% of diagnoses . The molecular heterogeneity within each
subtype has affected the success of biomarker discovery and may explain the variable responses to systemic
therapies . Therefore interpretation and validation of certain molecular markers will be key to further
[5]
enhancing the individualized management of RCC.