Abstract 4576: Study of the immune contexture in advanced pancreatic neuroendocrine tumors reveals tumor-associated macrophages as promoters of poor survival
Bibliographic record
Abstract
Abstract Introduction. PanNETs are characterized by heterogeneous but largely indolent growth, leading to advanced stage at diagnosis, difficulty predicting outcomes, and insufficiently effective treatments. A better understanding of PanNETs immune context is needed for rational immunotherapy strategies. The aim of this study was to characterize immune cell infiltrates within primary tumors, understand the correlation of immune infiltration with genes associated with PanNET development, and clinical-pathological features. Material and methods. Formalin-fixed paraffin-embedded (FFPE) surgically resected primary tumor specimens from 53 patients with metastatic PanNETs were evaluated for DAXX, ATRX, and immune-cell markers (CD8, CD4, CD45RO, FOXP3, ICOS, OX40, PD-1, LAG3, TIM-3, B7-H3, B7-H4, PD-L1, VISTA, and CD68) by immunohistochemistry (IHC). Intratumoral lymphocyte-enriched areas (LEA), defined by CD8 hot-spots, and macrophage-enriched areas (MEA), defined by CD68 hot spots, were selected for image analysis and cell densities were quantitated. We considered higher densities more than the third quartile value and low density as less or equal than the third quartile value for all the markers. 47 cases from the same FFPE tumor tissue blocks were used for paired-end RNA sequencing (HiSeq 4000 Sequencing System), and exome sequencing (T200 Platform) to MEN1, SETD2, MUTYH, CHEK2, BRCA2, ALT, DAXX, ATRX, PTEN, TSC1, and TSC2 genes. Differences between variables were analyzed by non-parametric t-test and Kaplan-Meier curves for time-to-event using SPSS statistical software version 24. Results. Overall, higher densities of CD8, CD4, CD68, and B7-H3 were found compared with the other markers. We found a significant correlation between CD8 in LEA with CD4 (r=0.7), FOXP3 (r=0.5), CD45RO (r=0.6), ICOS (r=0.5) and PD-1 (r=0.5) cell densities. In addition, CD68 in MEA had significant and positive correlation with TIM-3 (r=0.6) cell densities. Higher TIM-3 cell densities correlated with higher levels of TIM-3 (P=<0.00001), CD163 (P=0.004), and CSF1R (P=0.02) mRNAs. Patients with high CD68 and TIM-3 densities showed worse disease-specific survival (DSS). The ratio between CD68, TIM-3, B7-H3 and FOXP3 cell densities to CD8 positive cells was significantly higher in patients with loss of ATRX nuclear expression. We observed different gene mutations on those PanNET samples but only PTEN mutant tumors were associated with higher densities of CD68 and worst DSS compared with lowest CD68 and WT PTEN mutant tumors (P=0.002). Conclusions. TAMs were significantly correlated with inferior DSS in PanNETs. TAM depletion may, therefore, present an appealing and rational target for immunotherapeutic approaches in NETs. This work was funded by a Conquer Cancer Foundation of ASCO Career Development Award, and a grant from the Neuroendocrine Tumor Research Foundation. Citation Format: Alejandro Francisco-Cruz, Naohiro Uraoka, Suyu Liu, Edwin R. Parra, Luisa M. Solis, Barbara Mino, Arvind Dasari, Jaime Rodriguez-Canales, Michael J. Overman, Jonathan M. Loree, James C. Yao, Ignacio I. Wistuba, Daniel M. Halperin, Jeannelyn S. Estrella. Study of the immune contexture in advanced pancreatic neuroendocrine tumors reveals tumor-associated macrophages as promoters of poor survival [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4576.
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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 | 0.000 |
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".