ESMO Congress 2024 | OncologyPRO

Abstract 137P

Background

Establishing reliable and early predictive biomarkers of response of ICI is essential. Analysis of cfDNA fragmentation profiles (fragmentome) is a promising non-invasive method to do so independently of a specific molecular target, cancer type or treatment. We monitored plasmatic cfDNA concentration and size characteristics of the fragmentome in advanced lung, head and neck, kidney and bladder cancer patients, treated with ICI (n = 111). The aim was to predict EP (defined as progression at the first imaging evaluation) and PFS.

Methods

Our novel patented technology made possible to measure accurately cfDNA concentration and size profile directly from tens of microlitres of plasma and without prior DNA extraction (BIABooster system). Statistical association and predictive performances of response from fragmentome-derived metrics (e.g., concentration, size distribution peaks or fragments size ranges) were conducted. The data was split between a training (n=78) and a test (n=33) set. Optimal thresholds were determined through receiver-operator characteristics (ROC) curve analysis, and confidence intervals determined using bootstrap resampling. Classification metrics were assessed in both the training and testing set. The entire process was bootstrapped 100 times to assess the robustness.

Results

Quantity of long fragments over 1650 bp (LF) showed the best discriminatory power (AUC = 0.77 (0.65-0.87)) of EP. LF were significantly, strongly and positively associated with non-EP (odd ratio =0.27 (0.14-0.52), p <0.001) and longer PFS (p<0.001, hazard ration 0.406 (0.274 - 0.599)). The predictive performances of EP were also very high: AUC 0.75 (0.65-0.84), accuracy 71% (95% CI: 63% - 80%), positive predictive value was 0.61 (0.47-0.78), on the test set.

Conclusions

These findings highlight a very significant association of cfDNA high-molecular-weight fragments with EP and PFS that outperform the predictive value of the only routinely used marker PDL1.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

AP-HM.

Funding

Adelis France.

Disclosure

F. Ginot: Financial Interests, Personal, Full or part-time Employment, salary: Adelis; Financial Interests, Personal, Ownership Interest, I have equity within the company: ADELIS. A. Boutonnet: Financial Interests, Personal, Full or part-time Employment: Adelis. F. Fina: Financial Interests, Personal, Officer: ID Solutions Oncology, ID Solutions; Financial Interests, Personal, Ownership Interest: Adelis Technologies. All other authors have declared no conflicts of interest.