Abstract PO-061: Utilizing T cell receptor-based therapy to treat anaplastic thyroid cancer
Bibliographic record
Abstract
Abstract Anaplastic thyroid cancer (ATC) is considered to be among the most aggressive solid tumors in thyroid tissue, with a 6-month medium overall survival. The effectiveness of conventional treatments, such as surgery, chemotherapy, and radiation therapy, in extending the survival of patients is limited. Therefore, there is an urgent need to develop novel systemic therapeutic interventions that can induce long-lasting responses. Adoptive cell therapy has revolutionized cancer immunotherapy by successfully treating B-cell malignancies through chimeric antigen receptor-based approaches. For solid tumors, there is a need to identify a broader spectrum of tumor target antigens, and the field has now shifted towards leveraging T cell receptors (TCRs) which can recognize both intracellular and extracellular antigen-derived epitopes displayed by major histocompatibility complex (MHC) molecules. Our team has established an immunogenic epitope discovery pipeline, followed by a specialized protocol for empiric validation of candidate epitopes. We characterized immunogenic epitopes by coupling tandem mass spectrometry of MHC-eluted peptides with tumor proteome and MHC-peptide binding prediction databases. By integrating multi-omics data (genomics, transcriptomics, and immunopeptidomics) from both in-house and publicly available ATC databases, we find that ATC exhibits significant upregulation of pathways associated with microtubule-based movement, chromosome segregation, kinetochore complex components, and mitotic cytokinesis. We have identified several HLA-A2- and A24-restricted immunogenic peptides representing these pathway-associated proteins that covered more than 60% of the patient population. NDC80 kinetochore complex components (NDC80) and PDZ binding kinase (PBK) have been selected as top candidates. Peptides derived from NDC80 and PBK were subsequently utilized to isolate antigen-specific T cells from peripheral blood and identify cognate TCR. These peptide-specific T lymphocytes elicit cytotoxicity toward multiple HLA-matched ATC cell lines and tumor samples in vitro and in vivo. Furthermore, understanding the role of these genes in ATC tumorigenesis may identify novel combination strategies with adoptive cell therapy to yield synergistic effects. In conclusion, our studies contribute to the development of a new treatment paradigm for treating ATC, with the prospect of improving survival and outcome in this rare cancer patient population. Citation Format: Shao-Hsi Hung, Ying Henderson, Ke Pan, Yulun Chiu, Shailbala Singh, Yunyun Chen, Stephen Lai, Cassian Yee. Utilizing T cell receptor-based therapy to treat anaplastic thyroid cancer [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-061.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".