Abstract 3875: Investigating tumor-immune interactions in adult sarcomas of the extremities
Bibliographic record
Abstract
Abstract Introduction: Sarcoma is a heterogeneous group of connective tissue cancers with over 60 different subtypes. Curative treatment relies on surgical resection combined with radiation. In the event of metastasis, chemotherapy is commonly used but generally only with palliative intent. Given the heterogeneity of sarcomas, targeted therapies are limited and this has contributed to the relatively stagnant survival rates seen in the past decades. Objective: With poorly defined cancer antigens and genetic mutations, more personalized treatments, such as immunotherapy, and in particular adoptive cell transfer therapy (ACT), may be a more viable and promising option for select sarcoma patients than currently available palliative chemotherapy. As such, our study aims to create patient specific models to investigate the interactions between tumor-infiltrating lymphocytes (TILs) and autologous tumor cells. Methods: Over 250 tissue and blood samples from untreated sarcoma patients have been collected. The tissue samples are dissected and used for in vitro expansion of TILs or tumor cells. TIL cultures are characterized via flow cytometry and TIL responses are quantified using an IFNy ELISA. Tumor cultures are validated with RT-qPCR and dd-PCR to ensure tumor-specific mutations are retained. After characterizing and validating the cultures, autologous tumor cells and TILs are co-cultured to examine tumor-immune interactions. Outcomes of immune activity in the presence of tumor cells and tumorigenicity are evaluated to better understand the mechanisms that may be implicated in sarcoma immunotherapy. Results: At the end of a 3-week expansion period, of the 93 primary tumor samples cultured for TILs, only 7 did not yield any TIL growth; however, the final TIL yield varied between different patient samples, ranging from 0.005 - 83M cells. Both TIL cultures expanded from different samples of the same tumor and from tumors of different patients demonstrated variable cell proportions of CD4+ and CD8+ TILs. Some cultures also contained a proportion of CD56+ cells. ELISA documented TIL responses to stimulation in all collected cultures, indicating a viable and functional population. Of the 24 primary tumor samples cultured, 17 (8 of 10 undifferentiated pleomorphic sarcomas; 7 of 10 myxofibrosarcomas; 2 of 4 osteosarcomas) generated viable tumor cell cultures as defined by the presentation of stable growth beyond passage 5. Conclusion: Tumor cells and functional TILs can be isolated and expanded from most sarcomas; however, the methods must be optimized for each case. Further tumor culture validation by whole exome sequencing in combination with ddPCR is ongoing. A benchmark of an effective and clinically significant TIL yield will need to be better defined going forward. TILs are active in vitro and vary in population composition. Future experiments will focus on evaluating the killing capacity and tumor specificity of TILs. Citation Format: Alice Ko, Victoria Coward, Minji Lee, Kayley Xu, Nalan Gokgoz, Brendan Dickson, Jay Wunder, Irene L. Andrulis. Investigating tumor-immune interactions in adult sarcomas of the extremities [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3875.
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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) | 0.002 | 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".