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[2_TD$DIFF]

Letter to the

[3_TD$DIFF]

Editor

Re: Sumanta K. Pal, Guru Sonpavde, Neeraj Agarwal,

et al. Evolution of Circulating Tumor DNA Profile from

First-line to Subsequent Therapy in Metastatic Renal

Cell Carcinoma. Eur Urol 2017;72:557–64

Pal and coworkers

[1]

identified changes in the circulating

tumor DNA (ctDNA) profile in patients with metastatic

renal cell carcinoma (mRCC) and ctDNA fluctuations during

first-line and post first-line targeted therapy using a

HiSeq2500 sequencing system. To little surprise, a high

yield of genomic mutations (79%) was observed in this

heterogeneous enrichment malignancy, with gene muta-

tions of

TP53

(35%),

VHL

(23%),

EGFR

(17%),

NF1

(16%), and

ARID1A

(12%). The results indicate a significant increase in

mutation frequency in mRCC patients receiving targeted

therapy for subsequent therapeutic lines when compared

to first-line treatment, especially for

TP53

(49% vs 24%),

VHL

(29% vs 18%),

NF1

(20% vs 8%),

EGFR

(15% vs 8%), and

PIK3CA

(17% vs 8%). This largest study to date on ctDNA in mRCC

revealed that liquid biopsy has promise for guiding

targeted therapy. However, we feel that these results

deserve to be reconsidered with a view to revealing hidden

information behind this methodologically well-conducted

study.

Initially, the authors concluded that the frequency of

ctDNA mutations was higher in the post–first-line than in

the first-line setting. From basic principles, it is known

that the level of ctDNA mutations in the bloodstream is

determined by both release from tumor cells undergoing

necrosis, apoptosis, and active secretion, and engulfment

of scavenger cells such as macrophages

[2]

. However, a

subtle fact is that VEGF inhibitors could induce apoptosis

of renal cancer cells

[3] .

Hence, there is a great possibility

that the increase in mutation frequency partly results

from an increase in release caused by the inhibitor itself

rather than real changes in the tumor, and this probably

accounts for a considerable portion because of the large

tumor burden in mRCC. Moreover, mTOR inhibitors,

another major class, are responsible for induction of

macrophage inhibition, and even selective macrophage

death

[4]

. This apparently indicates that a decrease in

phagocytosis, as another confounding factor, may also

affect the mutation frequency. Therefore, the increase in

mutation frequency could possibly be an ‘‘illusion’’ and

might not totally reflect real levels of ctDNA, which seems

to be ignored by the authors, and new mutations may be

relatively more instructive.

In addition, a recent study suggested that the liver and

kidney are also involved in clearance of ctDNA

[5] .

Thus, we

recommend that the authors reanalyze their data and

consider intrinsic clearance and the glomerular filtration

rate, which were not taken into account in their study, to

obtain more comprehensive findings.

Furthermore, mutations for three significant genes,

PBRM1

,

BAP1

, and

KDM5C

, are potentially associated with

outcomes for crossover of targeted therapy according to a

previous study

[6]

, but these are not included in the

Guardant360 testing system. This disparity may introduce

bias when urologists use the Guardant360 platform to test

for ctDNA in mRCC.

In general, despite the merits of ctDNA in overcoming

heterogeneity via a scalpel-free method with real-time

analysis, many impact factors need to be taken into

consideration for use in clinical practice, especially for

guiding targeted therapy in mRCC patients.

Conflicts of interest:

The authors have nothing to disclose.

References

[1]

Pal SK, Sonpavde G, Agarwal N, et al. Evolution of circulating tumor DNA profile from first-line to subsequent therapy in metastatic renal cell carcinoma. Eur Urol 2017;72:557–64.

[2]

Holdenrieder S, Nagel D, Schalhorn A, et al. Clinical relevance of circulating nucleosomes in cancer. Ann N Y Acad Sci 2008;1137:180–9

.

[3]

Xin H, Zhang C, Herrmann A, et al. Sunitinib inhibition of Stat3 induces renal cell carcinoma tumor cell apoptosis and reduces immunosuppressive cells. Cancer Res 2009;69:2506–13.

[4]

Martinet W, Verheye S, De Meyer GR. Everolimus-induced mTOR inhibition selectively depletes macrophages in atherosclerotic pla- ques by autophagy. Autophagy 2007;3:241–4.

[5]

Yu SC, Lee SW, Jiang P, et al. High-resolution profiling of fetal DNA clearance from maternal plasma by massively parallel sequencing. Clin Chem 2013;59:1228–37. E U R O P E A N U R O L O G Y 7 2 ( 2 0 1 7 ) e 1 8 0 – e 1 8 1

available at

www.scienced irect.com

journal homepage:

www.europeanurology.com

DOI of original article:

http://dx.doi.org/10.1016/j.eururo.2017.03.046

.

http://dx.doi.org/10.1016/j.eururo.2017.07.009

0302-2838/

#

2017 European Association of Urology. Published by Elsevier B.V. All rights reserved.