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Gene expression meta-analysis reveals immune response convergence on the IFNγ-STAT1-IRF1 axis and adaptive immune resistance mechanisms in lymphoma.

Care MA, Westhead DR, Tooze RM - Genome Med (2015)

Bottom Line: Whether such coupled immune polarization and adaptive resistance is generalisable to lymphoid malignancies is incompletely defined.We validate and extend the results in an approach independent of "cell of origin" classification based on gene expression correlations across all data sets.Analysis of gene correlations across all data sets, independent of "cell of origin" class, demonstrates a consistent association with a hierarchy of immune-regulatory gene expression that places IDO1, LAG3 and FGL2 ahead of PD1-ligands CD274 and PDCD1LG2.

View Article: PubMed Central - PubMed

Affiliation: Section of Experimental Haematology, Wellcome Trust Brenner Building, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, LS9 7TF, UK.

ABSTRACT

Background: Cancers adapt to immune-surveillance through evasion. Immune responses against carcinoma and melanoma converge on cytotoxic effectors and IFNγ-STAT1-IRF1 signalling. Local IFN-driven immune checkpoint expression can mediate feedback inhibition and adaptive immune resistance. Whether such coupled immune polarization and adaptive resistance is generalisable to lymphoid malignancies is incompletely defined. The host response in diffuse large B-cell lymphoma (DLBCL), the commonest aggressive lymphoid malignancy, provides an empirical model.

Methods: Using ten publicly available gene expression data sets encompassing 2030 cases we explore the nature of host response in DLBCL. Starting from the "cell of origin" paradigm for DLBCL classification, we use the consistency of differential expression to define polarized patterns of immune response genes in DLBCL, and derive a linear classifier of immune response gene expression. We validate and extend the results in an approach independent of "cell of origin" classification based on gene expression correlations across all data sets.

Results: T-cell and cytotoxic gene expression with polarization along the IFNγ-STAT1-IRF1 axis provides a defining feature of the immune response in DLBCL. This response is associated with improved outcome, particularly in the germinal centre B-cell subsets of DLBCL. Analysis of gene correlations across all data sets, independent of "cell of origin" class, demonstrates a consistent association with a hierarchy of immune-regulatory gene expression that places IDO1, LAG3 and FGL2 ahead of PD1-ligands CD274 and PDCD1LG2.

Conclusion: Immune responses in DLBCL converge onto the IFNγ-STAT1-IRF1 axis and link to diverse potential mediators of adaptive immune resistance identifying future therapeutic targets.

No MeSH data available.


Related in: MedlinePlus

Integrated gene signature and ontology enrichment analysis demonstrates association of the COO-classified meta-profile with cell proliferation and B-cell signatures. a The top gene signature and ontology terms enriched in the COO-classified meta-profile, clustered according to the correlation of signatures given their gene membership. b The corresponding clustering of genes contributing to signature and ontology term enrichments for the COO-classified meta-profile, clustered according to correlation of genes given their signature membership. To the right general categories corresponding to major correlation clusters are illustrated. Corresponding high resolution versions are available in Additional files 7 and 8
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Fig2: Integrated gene signature and ontology enrichment analysis demonstrates association of the COO-classified meta-profile with cell proliferation and B-cell signatures. a The top gene signature and ontology terms enriched in the COO-classified meta-profile, clustered according to the correlation of signatures given their gene membership. b The corresponding clustering of genes contributing to signature and ontology term enrichments for the COO-classified meta-profile, clustered according to correlation of genes given their signature membership. To the right general categories corresponding to major correlation clusters are illustrated. Corresponding high resolution versions are available in Additional files 7 and 8

Mentions: In the COO-classified meta-profile a striking representation of genes linked to cell proliferation resulted in multiple distinct clusters of enriched terms reflecting a wide range of processes associated with cell proliferation (Fig. 2a; Additional file 7). In addition to this, distinct enrichment of signatures of the B-cell lineage was evident. From the gene perspective this was reflected in one main branch associated with cell cycle and cell proliferation, and the second including two principal subclusters associated on the one hand with RNA binding and processing, and on the other with core B-cell-associated genes (Fig. 2b; Additional file 8).Fig. 2


Gene expression meta-analysis reveals immune response convergence on the IFNγ-STAT1-IRF1 axis and adaptive immune resistance mechanisms in lymphoma.

Care MA, Westhead DR, Tooze RM - Genome Med (2015)

Integrated gene signature and ontology enrichment analysis demonstrates association of the COO-classified meta-profile with cell proliferation and B-cell signatures. a The top gene signature and ontology terms enriched in the COO-classified meta-profile, clustered according to the correlation of signatures given their gene membership. b The corresponding clustering of genes contributing to signature and ontology term enrichments for the COO-classified meta-profile, clustered according to correlation of genes given their signature membership. To the right general categories corresponding to major correlation clusters are illustrated. Corresponding high resolution versions are available in Additional files 7 and 8
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4566848&req=5

Fig2: Integrated gene signature and ontology enrichment analysis demonstrates association of the COO-classified meta-profile with cell proliferation and B-cell signatures. a The top gene signature and ontology terms enriched in the COO-classified meta-profile, clustered according to the correlation of signatures given their gene membership. b The corresponding clustering of genes contributing to signature and ontology term enrichments for the COO-classified meta-profile, clustered according to correlation of genes given their signature membership. To the right general categories corresponding to major correlation clusters are illustrated. Corresponding high resolution versions are available in Additional files 7 and 8
Mentions: In the COO-classified meta-profile a striking representation of genes linked to cell proliferation resulted in multiple distinct clusters of enriched terms reflecting a wide range of processes associated with cell proliferation (Fig. 2a; Additional file 7). In addition to this, distinct enrichment of signatures of the B-cell lineage was evident. From the gene perspective this was reflected in one main branch associated with cell cycle and cell proliferation, and the second including two principal subclusters associated on the one hand with RNA binding and processing, and on the other with core B-cell-associated genes (Fig. 2b; Additional file 8).Fig. 2

Bottom Line: Whether such coupled immune polarization and adaptive resistance is generalisable to lymphoid malignancies is incompletely defined.We validate and extend the results in an approach independent of "cell of origin" classification based on gene expression correlations across all data sets.Analysis of gene correlations across all data sets, independent of "cell of origin" class, demonstrates a consistent association with a hierarchy of immune-regulatory gene expression that places IDO1, LAG3 and FGL2 ahead of PD1-ligands CD274 and PDCD1LG2.

View Article: PubMed Central - PubMed

Affiliation: Section of Experimental Haematology, Wellcome Trust Brenner Building, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, LS9 7TF, UK.

ABSTRACT

Background: Cancers adapt to immune-surveillance through evasion. Immune responses against carcinoma and melanoma converge on cytotoxic effectors and IFNγ-STAT1-IRF1 signalling. Local IFN-driven immune checkpoint expression can mediate feedback inhibition and adaptive immune resistance. Whether such coupled immune polarization and adaptive resistance is generalisable to lymphoid malignancies is incompletely defined. The host response in diffuse large B-cell lymphoma (DLBCL), the commonest aggressive lymphoid malignancy, provides an empirical model.

Methods: Using ten publicly available gene expression data sets encompassing 2030 cases we explore the nature of host response in DLBCL. Starting from the "cell of origin" paradigm for DLBCL classification, we use the consistency of differential expression to define polarized patterns of immune response genes in DLBCL, and derive a linear classifier of immune response gene expression. We validate and extend the results in an approach independent of "cell of origin" classification based on gene expression correlations across all data sets.

Results: T-cell and cytotoxic gene expression with polarization along the IFNγ-STAT1-IRF1 axis provides a defining feature of the immune response in DLBCL. This response is associated with improved outcome, particularly in the germinal centre B-cell subsets of DLBCL. Analysis of gene correlations across all data sets, independent of "cell of origin" class, demonstrates a consistent association with a hierarchy of immune-regulatory gene expression that places IDO1, LAG3 and FGL2 ahead of PD1-ligands CD274 and PDCD1LG2.

Conclusion: Immune responses in DLBCL converge onto the IFNγ-STAT1-IRF1 axis and link to diverse potential mediators of adaptive immune resistance identifying future therapeutic targets.

No MeSH data available.


Related in: MedlinePlus