Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2020 Aug 11;12(8):758.
doi: 10.3390/pharmaceutics12080758.

Like a Rolling Stone: Sting-Cgas Pathway and Cell-Free DNA as Biomarkers for Combinatorial Immunotherapy

Affiliations
Review

Like a Rolling Stone: Sting-Cgas Pathway and Cell-Free DNA as Biomarkers for Combinatorial Immunotherapy

Guillaume Sicard et al. Pharmaceutics. .

Abstract

Combining immune checkpoint inhibitors with other treatments likely to harness tumor immunity is a rising strategy in oncology. The exact modalities of such a combinatorial regimen are yet to be defined, and most attempts have relied so far on concomitant dosing, rather than sequential or phased administration. Because immunomodulating features are likely to be time-, dose-, and-schedule dependent, the need for biomarkers providing real-time information is critical to better define the optimal time-window to combine immune checkpoint inhibitors with other drugs. In this review, we present the various putative markers that have been investigated as predictive tools with immune checkpoint inhibitors and could be used to help further combining treatments. Whereas none of the current biomarkers, such as the PDL1 expression of a tumor mutational burden, is suitable to identify the best way to combine treatments, monitoring circulating tumor DNA is a promising strategy, in particular to check whether the STING-cGAS pathway has been activated by cytotoxics. As such, circulating tumor DNA could help defining the best time-window to administrate immune checkpoint inhibitors after that cytotoxics have been given.

Keywords: biomarkers; combinatorial immunotherapy; cytotoxics; precision medicine.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Schematic representation of how immune checkpoint inhibitors work.
Figure 2
Figure 2
Sting/cGas Pathway.
Figure 3
Figure 3
Current use of biomarker prior to setting up combinatorial immunotherapy. Upfront testing helps to determine the Go/No Go by predicting the odds of success. However, no longitudinal monitoring is currently feasible and basal levels have to be considered as granted.
Figure 4
Figure 4
Proposed strategy for refining combinatorial immunotherapy. After that standard treatment is given, longitudinal monitoring of cell-free DNA helps to determine the best timing for further administering immune checkpoint inhibitors. Rather than pre-defined dosing, longitudinal monitoring allows customized treatment throughout time.

Similar articles

Cited by

References

    1. Barlési F., Scherpereel A., Rittmeyer A., Pazzola A., Tur N.F., Kim J.-H., Ahn M.-J., Aerts J.G., Gorbunova V., Vikström A., et al. Randomized Phase III Trial of Maintenance Bevacizumab with or without Pemetrexed after First-Line Induction with Bevacizumab, Cisplatin, and Pemetrexed in Advanced Nonsquamous Non–Small-Cell Lung Cancer: AVAPERL (MO22089) J. Clin. Oncol. 2013;31:3004–3011. doi: 10.1200/JCO.2012.42.3749. - DOI - PubMed
    1. Fitzhugh D.J., Lockey R.F. History of Immunotherapy: The First 100 Years. Immunol. Allergy Clin. N. Am. 2011;31:149–157. doi: 10.1016/j.iac.2011.03.003. - DOI - PubMed
    1. Kaufman H.L., Atkins M.B., Subedi P., Wu J., Chambers J., Mattingly T.J., Campbell J.D., Allen J., Ferris A.E., Schilsky R.L., et al. The promise of Immuno-oncology: Implications for defining the value of cancer treatment. J. Immunother. Cancer. 2019;7:129. doi: 10.1186/s40425-019-0594-0. - DOI - PMC - PubMed
    1. Ledford H. The perfect blend. Nature. 2016;532:162–165. doi: 10.1038/532162a. - DOI - PubMed
    1. Barbolosi D., Ciccolini J., Lacarelle B., Barlesi F., Andre N. Computational oncology—Mathematical modelling of drug regimens for precision medicine. Nat. Rev. Clin. Oncol. 2015;13:242–254. doi: 10.1038/nrclinonc.2015.204. - DOI - PubMed

Grants and funding