Abstract 4693: Characterization of the tumor immune microenvironment in head and neck squamous cell carcinoma (SCCHN)
Bibliographic record
Abstract
Abstract Approximately 20% of advanced SCCHNs respond to anti-PD-(L)1. We aimed to inform rational combination therapy development, which might have greater efficacy, by understanding the potential immune effects of the oncogenic human papillomavirus (HPV) in SCCHN, and by characterizing potentially targetable immune checkpoints in the tumor microenvironment (TME). Immunohistochemistry (IHC) was performed on archival SCCHN specimens from 27 treatment-naive patients. HPV testing with p16 IHC was confirmed by HPV genotyping. IHC for PD-L1 assessed percentage of positive tumor cells, and whether PD-L1 was expressed in an adaptive or constitutive pattern (i.e., PD-L1+ tumor cells juxtaposed to TILs or in the absence of TILs, respectively). PD-L1 on infiltrating immune cells was scored separately. IHC for CD3, CD4, CD8, CD20, CD68, FoxP3, PD-1, PD-L2, LAG-3, TIM-3, GITR and IDO was quantified using Halo image analysis for density of positive cells. Among 27 SCCHN specimens, 14 were HPV(-) and 13 were HPV+ (one HPV58, 12 HPV16). In 19 of 27 specimens (70%), ≥5% of tumor cells had PD-L1 cell surface expression by IHC, including 9 HPV+ and 10 HPV(-) cases. Among 23 tumors expressing any level of PD-L1 (≥1% tumor cells+), 12 displayed an adaptive PD-L1 expression pattern, 5 a constitutive pattern, and 6 were mixed. All tumors were infiltrated by immune cells (ICs). Notably, 26 of 27 specimens (96%) contained PD-L1+ immune cells (range 5-80% of ICs expressing PD-L1). The proportion of PD-L1+ ICs exceeded PD-L1+ tumor cells in 21/26 (81%) cases. Neither the proportion of PD-L1+ tumor cells nor infiltrating immune cells correlated with tumor viral status. When compared to HPV(-) tumors, HPV+ tumors contained significantly higher densities of CD3+, CD4+, CD8+, CD20+, and PD-1+ cells (p<0.02); there was a trend towards an increased density of FoxP3+ cells in HPV+ tumors. However, when comparing specimens in which tumor cells were PD-L1+ vs. (-), none of these markers were differentially expressed. This may reflect heterogeneous mechanisms driving constitutive vs. adaptive PD-L1 expression patterns in SCCHN. In addition to finding abundant IDO expression in these specimens (>500 IDO+ cells/mm2 in 17/27 specimens), IDO was expressed by tumor cells as well as ICs in 12/27 (44%) cases (range 5-95% tumor cells+). In summary, we found that both HPV+ and (-) SCCHNs abundantly express PD-L1 on tumor and/or stromal cells, although HPV+ tumors are more heavily infiltrated by ICs. Multiple other immune checkpoints are expressed in these tumors, providing options for therapeutic co-targeting. Tumor DNA sequencing is in progress to explore the genetic basis for constitutive vs. adaptive PD-L1 expression. These studies are expected to provide a comprehensive portrait of the SCCHN TME, with implications for future immunotherapy development. Funded by the Bristol-Myers Squibb International Immuno-Oncology Network and NCI R01 CA142779 Citation Format: Farah Succaria, Pia Kvistborg, Elizabeth L. Engle, Tracee L. McMiller, Elizabeth Thompson, Alan E. Berger, John Haanen, Suzanne L. Topalian, Janis M. Taube. Characterization of the tumor immune microenvironment in head and neck squamous cell carcinoma (SCCHN) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4693.
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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 | 0.001 | 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".