Abstract PO-072: Durvalumab in combination with radioactive iodine in recurrent/metastatic thyroid cancers: Update on clinical and correlative analyses
Bibliographic record
Abstract
Abstract Background: We hypothesized that radioactive iodine (RAI) can enhance the presentation of thyroid cancer immunogenic self- and neo-antigens to enhance the clinical benefit of immune checkpoint inhibitors (ICI). We conducted a phase 1 trial of RAI in combination with durvalumab (durva; anti-PD-L1) in patients (pts) with recurrent/metastatic (R/M) thyroid cancer. We report updated clinical outcomes and biological correlates performed on trial samples. Methods: Pts were required to have RECIST measurable R/M thyroid cancer with either >1 RAI-avid tumor(s) on the most recent RAI scan or one tumor with SUVmax <10 on FDG-PET. Prior therapies were allowed. Pts received durva 1500 mg IV every 4 weeks in combination with recombinant human TSH (rhTSH)-stimulated RAI (100 mCi) administered during cycle 1. Primary endpoint was safety and secondary endpoints included progression-free survival (PFS), defined as time from first durva dose until progression (PD) or death of any cause. Pre-treatment and on-treatment biopsies of the same target lesion were obtained from enrolled pts if feasible. Bulk RNA sequencing (RNAseq) was performed to assess transcriptomic characteristics of key tumor immune profiles and their correlation to PFS. Results: 11 pts enrolled; 7 pts underwent tumor biopsies. No dose-limiting toxicities or grade ≥3 adverse events related to drug were observed. BOR was 2 pts with partial responses, 7 pts with stable disease, and 2 pts with PD. Median PFS was 9.8 months with all patients eventually having PD events. Four pts had durable PFS >12 months. RNAseq analysis was performed on the tumor biopsies. Linear correlation analysis of transcriptome data from on-treatment tumors demonstrated a strong association between PFS and transcriptional scores for HLA expression (R2=0.76), MHC class I expression (R2=0.74), and NK/T cell cytolytic activity (CYT) (R2=0.69). The on-treatment tumors from pts with PFS >12 months had higher interferon-gamma (IFN-γ), HLA, MHC class I and CYT scores than pts with PFS<12 months (p<0.01). Baseline PD-L1 expression (normalized transcripts per million) was also significantly higher in pts with PFS>12 months (p=0.02). Detectable anti-TG and/or elevated anti-TPO (>1 IU/mL) autoantibody levels in pre-treatment serum samples (n=10) correlated with longer PFS on study treatment (p<0.03). RNAseq gene set enrichment analysis (GSEA) of on- vs pre-treatment samples showed durva-RAI increased thyroid autoimmunity gene sets in addition to the induction of IFN-γ and antigen presentation pathway. Conclusions: Durva-RAI has a favorable safety profile and is associated with prolonged PFS (>12 months) in a subset of pts with R/M thyroid cancer. Transcriptomic profiling reveals that durva-RAI enhancement of tumor antigen presentation and inflammation with T cell activation correlates to prolonged disease control. Enhancing pre-existing, subclinical autoimmunity against thyroid self-antigens may contribute to ICI efficacy. Further studies are needed to evaluate these hypotheses, including how RAI may contribute to ICI efficacy. Citation Format: Antoine Desilets, Winston Wong, Gnana P. Krishnamoorthy, Eric Jeffrey Sherman, Lara Dunn, Anuja Kriplani, James Vincent Fetten, Loren S. Michel, Erin McDonald, Ravinder K. Grewal, Mona Sabra, Laura Boucai, Stephanie Fish, Sofia Haque, Irina Ostrovnaya, Ronald A. Ghossein, James A. Fagin, David G. Pfister, Alan Loh Ho. Durvalumab in combination with radioactive iodine in recurrent/metastatic thyroid cancers: Update on clinical and correlative analyses [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Innovating through Basic, Clinical, and Translational Research; 2023 Jul 7-8; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2023;29(18_Suppl):Abstract nr PO-072.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".