Abstract PO-092: Molecular characterization of the salivary adenoid cystic carcinoma tumor immune landscape by anatomic subsite
Bibliographic record
Abstract
Abstract Introduction: Adenoid cystic carcinoma (AdCC) is typically indolent, however tends to behave more aggressively and present with perineural invasion and distant metastasis. Despite an improved understanding of AdCC pathobiology, the impact of anatomic tumor subsite (e.g., major versus minor salivary glands) on survival and response to treatment is relatively understudied. We recently discovered that submandibular AdCC’s exhibit unique differences in prognosis and treatment response to adjuvant radiotherapy. However, the impact of anatomic subsites on gene expression and immune cell composition, has not been investigated. Materials and methods: We used 4 publicly available AdCC molecular datasets (n = 37 AdCCs of different origin: 27 primary and 10 metastatic; 7 parotid (PG), 5 submandibular (SMG), 4 sublingual (SLG), 21 minor salivary gland (mG) and 21 normal salivary gland tissue samples). Data were harmonized between datasets using identical quantification procedures, followed by filtering and normalization performed simultaneously on the pooled data from all cohorts. Gene set enrichment analysis (GSEA) was performed Human Molecular Signatures Database (MSigDB) Hallmark and Oncologic signatures. Tumor immune microenvironment (TIME) decomposition was performed using a non-negative matrix factorization-based approach. GSEA and TIME differences between AdCC subsites were evaluated using Wilcoxon rank-sum and nonparametric equality-of-medians tests. Results: We identified different levels of enrichment for several key tumorigenic pathways between AdCCs arising within different anatomic subsites. Among AdCCs, major glands overexpressed the HALLMARK_SPERMATOGENESIS signature (parotid and sublingual glands), while the HALLMARK_REACTIVE_OXYGEN_SPECIES_PATHWAY (ROS) signature was significantly underexpressed in SMG AdCCs. In addition, the HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION (EMT) signature was significantly underexpressed in both SMG and PG AdCCs. These pathway signatures were not seen in control tissue comparison samples, indicating that these features are AdCC-specific. Additionally, TIME decomposition identified differences in CD4-T cell populations (minor > major gland AdCC) and natural killer (NK) cells (increased in PG and SLG). Meanwhile, normal control comparisons revealed a significant increase in plasma cells only within SM glands. Conclusions: AdCC subsites exhibit survival and treatment-response differences, and in this study demonstrate that these anatomical sites are associated with distinct molecular features. Specifically, these different anatomical sites vary in the expression of spermatogenesis, ROS, and EMT signature-related genes. Also, CD4-T and NK cell populations vary by anatomical site, suggesting that the SMG AdCC tumor-intrinsic pathway differences observed may be responsible for influencing the TIME composition and increased prognosis associated with these tumors following adjuvant radiotherapy. Validation with additional cohorts of primary AdCCs with accurate clinical annotation are required. Citation Format: Jason Tasoulas, Travis Schrank, Steven Johnson, Kimon Divaris, Stamatios Theocharis, Trevor Hackman, Siddharth Sheth, Kedar Kirtane, Juan Hernandez-Prera, Christine Chung, Wendell Gray Yarbrough, Natalia Issaeva, Antonio Amelio. Molecular characterization of the salivary adenoid cystic carcinoma tumor immune landscape by anatomic subsite [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-092.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".