Molecular biomarkers to identify patients (pts) who may benefit from durvalumab (D; anti-PD-L1) ± tremelimumab (T; anti-CTLA-4) in recurrent/metastatic head and neck squamous cell carcinoma (R/M HNSCC) from HAWK and CONDOR studies.
Bibliographic record
Abstract
6548 Background: Baseline tumor and germline biomarkers in R/M HNSCC were analyzed for predictive potential in pts benefitting from D or D+T. Methods: In HAWK (NCT02207530), 112 pts (PD-L1 tumor cells [TC]≥25%) received D (10 mg/kg Q2W for ≤12 m); in CONDOR (NCT02319044), 67 pts (PD-L1 TC < 25%) received D (10 mg/kg Q2W for ≤12 m), 133 pts received D+T (D 20 mg/kg Q4W, T 1 mg/kg Q4W for ≤12 m), and 67 pts received T (10 mg/kg Q4W [7 doses] then Q12W [2 doses] for ≤12 m) VENTANA PD-L1 (SP263) Assay determined PD-L1 status. Paired FFPE archival tumor and PBMC samples (as germline control) in the HAWK and CONDOR trials were evaluated by whole exome sequencing (WES). Tumor mutation burden (TMB) was number of somatic mutations/megabase. HLA class I types were obtained via WES of PBMCs (CONDOR only). HPV and neutrophil-to-lymphocyte ratio (NLR) were tested locally in CONDOR. Wilcoxon, log-rank tests, and COX-PH models were used. Pooled D & D+T data were analyzed unless noted. Results: 153 pts had paired evaluable FFPE tumor and PBMC samples (HAWK, n = 48; CONDOR, n = 105). TMB distributions were similar between studies ( P= 0.43). TMB correlated with smoking ( P= 0.02) but not HPV ( P= 0.24), NLR ( P= 0.66), or PD-L1 status ( P= 0.43). Overall, high TMB (≥upper tertile) trended with longer OS vs low TMB in all evaluable pts (N = 153; 9.0 vs 5.6 m; HR = 0.70; 95% CI = 0.48-1.01); P= 0.06). In HAWK, there was no association of TMB with OS. In CONDOR, pts (D and D+T arms) with high TMB vs low had significantly longer OS (N = 76; 16.3 vs 5.3 m; HR = 0.53; 95% CI = 0.31-0.92). TMB and OS association was further assessed by increasing TMB cutoffs. Improved HRs trended with higher cutoffs; cutoffs ≥upper quartile significantly linked to OS.TMB was not associated with PFS or ORR. Pts with low PD-L1 and low TMB had worse OS compared to pts with high PD-L1 or high TMB. Pts with high NLR (≥median) and low TMB had significantly worse OS than pts with low NLR and high TMB (HR = 2.63, P< 0.001). Analysis of germline HLA alleles revealed significantly poorer survival for carriers of the HLA-B*15:01 allele (9.4%) (HLA-B variant status did not affect TMB and OS association in CONDOR). Germline HLA heterozygosity did not impact OS. Pts with mutations in ATM (5%), a DNA damage repair gene, also trended with prolonged OS. Conclusions: TMB is a possible predictive biomarker of IO HNSCC therapy. Combined analysis of NLR and TMB may provide additional PD-L1 data in assessing pts most likely to have long-term benefit. Clinical trial information: NCT002207530, NCT02319044 .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".