Another topic that remains to be discussed is CNV detection.
Since tumor-specific DNA is only a small part of cfDNA, copy
number change in tumor cells only leads to slight copy number
difference in the ctDNA sequencing data. For instance, if tumor-
specific DNA is 1% of the whole cfDNA, and copy number fold in
the tumor cells is five, the copy number in whole cfDNA data will
be 104%, which is just slightly higher than average level. Current
CNV detectors, like CNVkit, are not designed to deal with ctDNA
sequencing data and are not sensitive enough to detect such subtle
changes in CNV. Better CNV detectors remain to be developed,
which should provide better normalization for deep and target-
captured ctDNA sequencing data.
Some new methods targeting for cancer immunology are draw-
ing attraction recently. One topic is to predict the outcome of
cancer immunotherapies, especially PD-1/PD-L1 checkpoint inhi-
bitors. Tumor mutation burden (TMB) has been shown to be
associated with the response of cancer immunotherapies. However,
TMB is usually calculated with tissue whole exome sequencing
data, and calculating TMB with ctDNA is still challenging due to
the low MAF and high level of noises. Methods optimized for
ctDNA-based TMB calculation are needed, and this topic can be
discussed in future. Another topic related to cancer immunother-
apy is neoantigen discovery. In December 2016, Parker Institute
for Cancer Immunotherapy and others announced the formation of
the Tumor Neoantigen Selection Alliance. This alliance involves
researchers from 30 nonprofit institutions and aims to identify
software that can best predict neoantigens from patient tumor
DNA. For now, computational prediction of neoantigens capable
of eliciting efficacious antitumor responses in patients remains a hit-
or-miss affair. It is even much more challenging to do the same
prediction from patient’s ctDNA. The neoantigen prediction study
will be a hot topic in both academic and industrial communities,
and the progress and outcome can be discussed in the future.References
- Kohler CBZ, Radpour R et al (2011) Cell-free
DNA in the circulation as a potential cancer
biomarker. Anticancer Res 31:2623–2628 - Diehl F, Schmidt K, Choti MA, Romans K,
Goodman S, Li M, Thornton K, Agrawal N,
Sokoll L, Szabo SA, Kinzler KW, Vogelstein B,
Diaz LA Jr (2008) Circulating mutant DNA to
assess tumor dynamics. Nat Med 14
(9):985–990. https://doi.org/10.1038/nm.
1789 - Heitzer E, Ulz P, Geigl JB (2015) Circulating
tumor DNA as a liquid biopsy for cancer. Clin
Chem 61(1):112–123. https://doi.org/10.
1373/clinchem.2014.222679
4. Leon SASB, Sklaroff DM et al (1977) Free
DNA in the serum of cancer patients and the
effect of therapy. Cancer Res 37:646–650
5. Beaver JA, Jelovac D, Balukrishna S, Cochran
RL, Croessmann S, Zabransky DJ, Wong HY,
Valda Toro P, Cidado J, Blair BG, Chu D,
Burns T, Higgins MJ, Stearns V, Jacobs L,
Habibi M, Lange J, Hurley PJ, Lauring J, Van-
DenBerg DA, Kessler J, Jeter S, Samuels ML,
Maar D, Cope L, Cimino-Mathews A,
Argani P, Wolff AC, Park BH (2014) Detection
of cancer DNA in plasma of patients with early-
stage breast cancer. Clin Cancer Res 20
(10):2643–2650. https://doi.org/10.1158/
1078-0432.CCR-13-2933
92 Shifu Chen et al.