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Endocrine and neuroendocrine tumours

1869 - Immune Landscape of Pancreatic Neuroendocrine Tumours (PanNETs)

Date

10 Sep 2017

Session

Endocrine and neuroendocrine tumours

Presenters

Kate Young

Citation

Annals of Oncology (2017) 28 (suppl_5): v142-v157. 10.1093/annonc/mdx368

Authors

K. Young1, C. Ragulan2, G. Nyamundanda2, Y. Patil2, R.T. Lawlor3, D. Cunningham1, N. Starling1, A. Scarpa3, A. Sadanandam2

Author affiliations

  • 1 Gi And Lymphoma Research Department, The Royal Marsden NHS Foundation Trust, SM2 5PT - Sutton/GB
  • 2 Molecular Pathology, The Institute of Cancer Research, SM2 5NG - Sutton/GB
  • 3 Arc-net Centre For Applied Research On Cancer, University and Hospital Trust of Verona, Verona/IT
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Abstract 1869

Background

To date little is known about the immune landscape of PanNETs and if immunotherapy could play a role in their treatment. We previously identified 3 molecular subtypes in PanNETs: Metastases like primary (MLP), intermediate and insulinoma like tumours (PanNETassigner signature, Sadanandam Cancer Discovery 2015). Here we sought to profile the immune architecture of 48 PanNET patient samples across these subtypes.

Methods

Patients were recruited by the ARC-Net Research Centre Verona, within an ethically approved protocol. Quality RNA was isolated from fresh frozen samples for immune profiling using microarrays, nCounter platform (Nanostring Technology) and RNAseq (Illumina). CIBERSORT analysis was performed to assess immune cell enrichment.

Results

48 PanNET samples were classified using the PanNETassigner gene signature. Based on immune expression profile analysis, tumours were divided into two categories, immune high or immune dormant. The majority of the MLP subtype were immune high, whereas most of the insulinoma and intermediate samples were immune dormant. A small number of insulinoma samples were immune high reflecting the heterogeneity of this tumour. Within the MLP subtype there was increased expression of CD8B, LAG3, CD38, CXCL10, CXCL9, CCL19, CD28 and CD27 compared to the other subtypes. Some of these genes are associated with chronic infection (CD38, CXCL10) whilst others are markers of T cell exhaustion (LAG3). This pattern is consistent with CIBERSORT analysis conducted using microarray data on an overlapping cohort of PanNET samples, where the MLP subtype was associated with increased levels of infiltrating T cells but also an increase in exhausted CD8+ve T cells. PD1 was highly expressed in 2/15 MLPs. PDL1 expression was heterogeneous in MLP but high in 7/13 insulinomas. FOXP3 was highly expressed in a subset of the MLP samples (7/16).

Conclusions

We have demonstrated the differential expression of immune related genes across 3 known PanNET subtypes. The MLP subtype appears to be associated with an immune profile similar to that seen in chronic infection with increased T-cell exhaustion. Such detailed profiling is essential to inform patient selection approaches for immunotherapy and rational immunotherapy combinations for panNETs in the future.

Clinical trial identification

Legal entity responsible for the study

Institute of Cancer Research

Funding

NIHR Biomedical Research Centre at The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London

Disclosure

All authors have declared no conflicts of interest.

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