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Updated: Dec 11, 2025
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Like a Rolling Stone: Sting-Cgas Pathway and Cell-Free DNA as Biomarkers for Combinatorial Immunotherapy
Guillaume Sicard1, Frédéric Fina2, Raphaelle Fanciullino1
1SMARTc Unit, CRCM Inserm U1068, Aix Marseille University, 13007 Marseille, France.
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.
Insights
Combining immune checkpoint inhibitors with other cancer treatments requires precise timing. Monitoring circulating tumor DNA may reveal optimal windows for sequential drug administration, enhancing treatment efficacy.
Area of Science:
- Oncology
- Immunotherapy
- Biomarker Research
Background:
- Immune checkpoint inhibitors (ICIs) combined with other therapies are a key strategy in oncology.
- Current combination regimens often use concomitant dosing, lacking optimal timing.
- Immunomodulatory effects are time-, dose-, and schedule-dependent, necessitating real-time biomarkers.
Purpose of the Study:
- To review putative biomarkers for optimizing ICI combination therapy timing.
- To explore how biomarkers can guide sequential administration of treatments.
Main Methods:
- Review of current literature on biomarkers for ICI therapy.
- Analysis of predictive markers, including PD-L1 expression and tumor mutational burden.
- Focus on circulating tumor DNA (ctDNA) as a dynamic biomarker.
Main Results:
- Current biomarkers like PD-L1 and tumor mutational burden are insufficient for timing ICI combinations.
- Monitoring ctDNA shows promise for assessing pathway activation, such as the STING-cGAS pathway post-cytotoxic therapy.
- ctDNA may help determine optimal windows for ICI administration after cytotoxic agents.
Conclusions:
- There is a critical need for real-time biomarkers to guide the optimal timing of combining ICIs with other drugs.
- Circulating tumor DNA monitoring is a promising strategy to identify these optimal time-windows.
- This approach could enhance the efficacy of combinatorial cancer immunotherapy regimens.
