Abstract A038: Targeting TCTP overcomes resistance to T cell-mediated immunotherapy by reversing the multi-malignant phenotypes of immune-refractory tumor cells
Bibliographic record
Abstract
Abstract Cancer immunotherapy, particularly T cell-mediated therapy such as immune checkpoint blockade (ICB) and adoptive T cell transfer (ACT), has shifted the paradigm for cancer treatment. However, the emergence of immune-refractory tumor has limited its clinical success by disrupting one or more steps of the cancer immunity cycle. In addition, multi-malignant phenotypes of immune-refractory tumor cells are also one of the major causes result poor prognosis of patients. We need to identify novel predictive biomarker allowing for the selection of patients who will receive clinical benefit from immune-refractory tumors. Therefore, identifying the immune-resistance and multi-malignant factor, which not only can be targeted by clinically available medicines is very important. Here, we identified TCTP as a novel factor conferring multi-malignant phenotypes of immune-refractory tumor cells. We discovered a vital role of TCTP at the crossroads between multi-malignant tumor cells and the anti-cancer immunity system by demonstrating that TCTPhigh tumor cells enriched by immune selection pressure drive immune-refractory phenotypes. Importantly, the expression levels of TCTP within the tumors significantly associated with the clinical response of anti-PD-L1 therapy, which suggest TCTP as a prognostic marker in the case of clinical trials. Furthermore, targeting TCTP by clinical available drug overcomes the resistance to T cell-mediated therapy including ICB and ACT. Thus, our findings demonstrated that TCTP could be a both a valid target a prognostic marker providing a framework for patient selection to apply combined therapy of T cell-mediated therapy with TCTP-targeting drugs. Citation Format: Tae Woo Kim. Targeting TCTP overcomes resistance to T cell-mediated immunotherapy by reversing the multi-malignant phenotypes of immune-refractory tumor cells [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr A038.
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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 | 0.000 | 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 | 0.001 |
| 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".