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Theranostics 2021; 11(8):3565-3579. doi:10.7150/thno.54343 This issue Cite

Research Paper

The immune contexture of primary central nervous system diffuse large B cell lymphoma associates with patient survival and specific cell signaling

Melissa Alame^1,2,3,4, Emmanuel Cornillot^1,3,4*, Valère Cacheux^2,5*, Valérie Rigau^5,6, Valérie Costes-Martineau^5,6, Vanessa Lacheretz-Szablewski^5,6✉, Jacques Colinge^1,4,5✉

1. Institut de Recherche en Cancérologie de Montpellier (IRCM), INSERM U1194, Parc Euromédecine, 208 rue des Apothicaires, 34298 Montpellier, France.
2. Biological Hematology Department, Montpellier University Hospital, Saint Eloi Hospital, 34275 Montpellier, France.
3. Université de Montpellier, Faculté de Pharmacie, 15 avenue Charles Flahault, 34093 Montpellier, France.
4. Institut régional du Cancer Montpellier (ICM), Parc Euromédecine, 208 rue des Apothicaires, 34298 Montpellier, France.
5. Université de Montpellier, Faculté de Médecine, 2 rue école de Médecine, 34060 Montpellier, France.
6. Département de pathologie et d'oncologie biologique, Montpellier University Hospital, Gui De Chauliac Hospital, 34000 Montpellier, France.
*Equal contributions to this work.

✉ Corresponding authors: E-mail: jacques.colingefr; v-szablewskifr.

Abstract

Rationale: Primary central nervous system diffuse large B-cell lymphoma (PCNSL) is a rare and aggressive entity that resides in an immune-privileged site. The tumor microenvironment (TME) and the disruption of the immune surveillance influence lymphoma pathogenesis and immunotherapy resistance. Despite growing knowledge on heterogeneous therapeutic responses, no comprehensive description of the PCNSL TME is available. We hence investigated the immune subtypes of PCNSL and their association with molecular signaling and survival.

Methods: Analysis of PCNSL transcriptomes (sequencing, n = 20; microarrays, n = 34). Integrated correlation analysis and signaling pathway topology enabled us to infer intercellular interactions. Immunohistopathology and digital imaging were used to validate bioinformatic results.

Results: Transcriptomics revealed three immune subtypes: immune-rich, poor, and intermediate. The immune-rich subtype was associated to better survival and characterized by hyper-activation of STAT3 signaling and inflammatory signaling, e.g., IFNγ and TNF-α, resembling the hot subtype described in primary testicular lymphoma and solid cancer. WNT/β-catenin, HIPPO, and NOTCH signaling were hyper-activated in the immune-poor subtype. HLA down-modulation was clearly associated with a low or intermediate immune infiltration and the absence of T-cell activation. Moreover, HLA class I down-regulation was also correlated with worse survival with implications on immune-intermediate PCNSL that frequently feature reduced HLA expression. A ligand-receptor intercellular network revealed high expression of two immune checkpoints, i.e., CTLA-4/CD86 and TIM-3/LAGLS9. TIM-3 and galectin-9 proteins were clearly upregulated in PCNSL.

Conclusion: Altogether, our study reveals that patient stratification according to immune subtypes, HLA status, and immune checkpoint molecule quantification should be considered prior to immune checkpoint inhibitor therapy. Moreover, TIM-3 protein should be considered an axis for future therapeutic development.

Keywords: PCNSL, immune contexture, bioinformatics, immunotherapy, cellular interactions

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