Abstract 1226P
Background
Data suggest ctDNA detection in the weeks following curative treatment is predictive of outcome in early-stage NSCLC, potentially guiding adjuvant treatment. Clinically, it would be convenient if samples collected before or shortly after resection were predictive, even when sample is limited and ctDNA levels are low.
Methods
We investigated the value of plasma collected pre- and 1-3 days after treatment (d1-3), in patients from the LEMA and LUCID studies, tested using RaDaR®. Tumor exome sequencing (WES) guided assay design.
Results
In LEMA, 99% of surgical resection and 77% of diagnostic biopsies yielded sufficient DNA for WES and assay design. ctDNA was detected pre-treatment in 48% of 87 patients, with median eVAF 0.02%. Detection rose with stage; 19%, 64% and 92% in I, II and III, as did median eVAF; 0.01%, 0.02% and 0.06%. These data were comparable to LUCID (Gale et al, 2022), with ctDNA detected in 51% patients, including 24%, 77% and 87% with stage I, II and III. Considering both cohorts, pre-treatment ctDNA associated with reduced recurrence free- (RFS; HR=2.5; 95% CI 1.5-4.2, p<0.001) and overall- survival (OS; 2.04; 1.1-3.7, p=0.02). Sensitivity, specificity, positive- (PPV) and negative- predictive value (NPV) were 66%, 60%, 49% and 75%. Pre-treatment ctDNA was detected with eVAF as low as 0.0008%. Underlining the value of detection to such levels, we observed worse RFS (2.5; 1.3-5.0, p=0.01) and OS (2.3; 1.1-4.9, p=0.03) in patients with pre-treatment ctDNA detected at <0.01% vs. ctDNA negative patients. Detection <0.01% was possible with as little as 0.7mL plasma and ∼4ng DNA input. Compared to pre-treatment, d1-3 ctDNA was detected as low as 0.00002% eVAF, in 19% of 80 samples, and was associated with worse RFS (8.6; 3.8-19.6, p>0.001) and OS (11.2; 4.2-30.2, <0.001). Sensitivity, specificity, PPV and NPV were 44%, 89%, 53% and 85%.
Conclusions
We show sensitive tumor-informed detection of ctDNA is possible even from ‘real-world’ samples of suboptimal quantity, and is prognostic in samples collected before and soon after treatment. The predictive value of ctDNA may be useful to guide (neo)adjuvant treatment. An expanded analysis will be presented.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
NeoGenomics.
Disclosure
C.G. Smith: Other, Institutional, Full or part-time Employment: NeoGenomics. R. Rintoul: Financial Interests, Institutional, Speaker, Consultant, Advisor: Olympus Medical; Non-Financial Interests, Institutional, Leadership Role: UK Lung Cancer Coalition; Non-Financial Interests, Institutional, Research Grant, Project grant funding to institution: Asthma and Lung UK, UKRI Medical Research Council, Cancer Research UK; Non-Financial Interests, Institutional, Funding, Salary support: NIHR Cambridge Biomedical Research Centre, Cancer Research UK. K. Monkhorst: Non-Financial Interests, Institutional, Speaker, Consultant, Advisor, Consulting fees. To my institution: Lily, Bayer, Amgen. N. Rosenfeld: Non-Financial Interests, Institutional, Funding, Institution: Cancer Research UK, University of Cambridge, Cambridge University Hospitals, Royal Papworth Hospital; Non-Financial Interests, Institutional, Funding, In-kind contribution: NeoGenomics Ltd, Inivata Ltd; Non-Financial Interests, Institutional, Research Grant, Grants to institution: Cancer Research UK, UKRI, AstraZeneca; Financial Interests, Personal and Institutional, Royalties: Inivata Ltd, NeoGenomics Ltd; Non-Financial Interests, Personal, Speaker, Consultant, Advisor, Consulting fees: Inivata Ltd; Financial Interests, Personal, Stocks/Shares: NeoGenomics Ltd, Inivata Ltd. All other authors have declared no conflicts of interest.
Resources from the same session
1111P - Genomic and transcriptomic analysis of Japanese melanoma reveals candidate biomarkers for immune checkpoint inhibitor responders
Presenter: Toshihiro Kimura
Session: Poster session 04
1112P - Immunotherapy after progression to double immunotherapy: Pembrolizumab and Lenvatinib versus conventional chemotherapy for patients with metastatic melanoma after failure of PD-1/CTLA-4 inhibition
Presenter: Dimitrios Ziogas
Session: Poster session 04
1113P - A machine learning model based on computed tomography radiomics to predict prognosis in subjects with stage IV melanoma
Presenter: Maria Teresa Maccallini
Session: Poster session 04
1114P - Deciphering unresectable in-transit metastasis in melanoma: Multi-modal and longitudinal insights
Presenter: Giuseppe Tarantino
Session: Poster session 04
1115P - Multiomics clustering of patients with cutaneous melanoma to reveal survival trends based on tumor immune evasion features
Presenter: Adeliya Leleytner
Session: Poster session 04
1116P - Application of the Scottish inflammatory prognostic score to the south-east Scotland cancer network real-world melanoma cohort
Presenter: Karim El-Shakankery
Session: Poster session 04
1117P - Intratumoral microbiota is associated with prognosis in Chinese patients with skin melanoma
Presenter: Hang Jiang
Session: Poster session 04
1118P - Immunological alterations during neoadjuvant BRAF/MEK inhibition in patients with prior unresectable regionally advanced melanoma: Translational analysis from the REDUCTOR trial
Presenter: Femke Burgers
Session: Poster session 04
1119P - Genomic and transcriptomic predictors of resistance to anti-PD1 monotherapy in patients with advanced melanoma
Presenter: Wenya Wang
Session: Poster session 04
1120P - Tumoral and peripheral immunophenotype of patients with stage II/III melanoma undergoing adjuvant immunotherapy following tumor resection
Presenter: Maria Ascierto
Session: Poster session 04