Abstract A007: Resident memory T cells express PD-1 in high grade liposarcoma
Bibliographic record
Abstract
Abstract Objective: Memory T cells play crucial roles in anti-tumor immunity. Tumor-associated resident memory T cells (TRM) have been associated with durable immune response and improved patient survival across multiple tumor types. SARC028, a phase II, multicenter trial of pembrolizumab, a programmed death 1 (PD-1) checkpoint inhibitor immunotherapy, showed promising activity in select histologic subtypes of advanced soft tissue sarcoma (STS), including dedifferentiated liposarcoma (DDLPS). However, there was only a 20% overall response rate. Notably, the patients who did respond to immunotherapy had durable responses, supporting our enthusiasm to understand the potential role for TRM in liposarcoma anti-tumor immunity. The characterization of memory T cells in liposarcoma, and whether TRM are present has not been explored. Design: Fresh retroperitoneal liposarcoma specimens from 8 patients: 3 well-differentiated liposarcoma (WDLPS) and 5 DDLPS were collected. Lymphocytes were analyzed by flow cytometry using T-cell (CD45, CD3, CD4, CD8) and phenotypic markers (CD69, CD62L, CD103, CD49a, PD-1, TIM-3). Results: DDLPS had a 4-fold higher overall T-cell infiltration and a 2.5-fold higher CD8+/CD4+ T-cell ratio than WDLPS. DDLPS contained CD8+ T cells with a CD45RA− CCR7− CD69hi CD62Llo phenotype, characteristic of a TRM response, and well as CD69lo effector memory T (TEM) cells. DDLPS had 3-fold more TRM than WDLPS. DDLPS had a much higher level of activated PD-1+ CD69+ CD8+ resident memory T-cell population compared to WDLPS. Additionally, the population of TRM had higher PD-1 expression compared to TEM in both DDLPS and WDLPS. Conclusions: These data suggest that TRM subsets may contribute to the responsiveness to anti-PD1 therapy in patients with DDLPS. Further investigations may lead to the discovery of TRM-targeted T-cell therapies in DDLPS, which currently has limited treatment options. Citation Format: Christina V. Angeles, Jichang Han, Jodi Wilkoswki, Scott Bresler. Resident memory T cells express PD-1 in high grade liposarcoma [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr A007.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".