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  • Poster presentation
  • Open Access

Co-expression networks identify distinct immune infiltrates in hepatocellular carcinoma

  • 1 and
  • 1
Journal for ImmunoTherapy of Cancer20153 (Suppl 2) :P213

https://doi.org/10.1186/2051-1426-3-S2-P213

  • Published:

Keywords

  • Hepatic Stellate Cell
  • Immune Checkpoint
  • Cell Module
  • Adjacent Liver
  • CTNNB1 Mutation

Background

The vast majority of hepatocellular carcinoma (HCC) arise in the context of chronic inflammation, especially with hepatitis B or hepatitis C viral infection. Several studies have identified prognostic immune biomarkers in HCC tumors and peritumoral regions. Recently, a Phase 1 trial of a PD-1 inhibitor has demonstrated efficacy in HCC. In order to characterize the diversity of immune microenvironments in HCC, we investigated co-expression networks of immune lineage-specific genes.

Results

We conducted a meta-analysis of gene expression data from over 500 HCC tumors and matched adjacent liver specimens. PD-L1 and PD-L2 had higher RNA levels in adjacent liver, compared with tumors. Tumoral expression of PD-L1 and PD-L2 were correlated with macrophage lineage genes. We identified 3 major co-expression network modules that corresponded with different immune cell sub-types: (1) An infiltrating T cell module was enriched for TCR activation, recruitment chemokines and elevated immune checkpoints. (2) A hepatic stellate cell module was associated with extracellular matrix remodeling, epithelial-to-mesenchymal transition and TGF-beta signaling. (3) A macrophage module had elevated macrophage lineage genes. By integrating these co-expression modules with HCC molecular sub-classes, the infiltrating T cell signature was enriched in the Hoshida S1 subclass1 and Chiang interferon subclass2, and was less prevalent among HCC with CTNNB1 mutations.

Conclusion

Transcriptomic analyses revealed immune cell types and potential regulators in HCC. The joint profiling of infiltrating immune sub-types and genetic alterations may guide the selection of combination therapies.

Authors’ Affiliations

(1)
Novartis Institutes for Biomedical Research, Cambridge, MA, USA

References

  1. Hoshida Y, et al: Cancer Research. 2009, 69: 7385-7392.PubMedPubMed CentralView ArticleGoogle Scholar
  2. Chiang DY, et al: Cancer Research. 2008, 68: 6779-6788.PubMedPubMed CentralView ArticleGoogle Scholar

Copyright

© Chiang and Huang 2015

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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