Immune Heterogeneity of Glioblastoma Subtypes: Extrapolation from the Cancer Genome Atlas

Doucette, Tiffany; Rao, Ganesh; Rao, Arvind; Шен, Ли; Aldape, Kenneth; Wei, Jun; Dziurzynski, Kristine; Gilbert, Mark R.; Heimberger, Amy B.

doi:10.1158/2326-6066.cir-13-0028

Cited by 198 publications

(194 citation statements)

References 40 publications

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“…37 However, their occurrence in FL and DLBCL had not been reported previously, and their combination might differ from those evolved by other cancers. 38 Indeed, transcriptomes from biopsies do not identify which cells in these samples are expressing the immune checkpoint molecules. Therefore, our IHC study not only confirmed the expression of immune-evasion at the protein level, but also specified their respective distribution pattern, whether in tumor cells themselves or in their immune infiltrates.…”

Section: E1026530-8 Volume 4 Issue 8 Oncoimmunologymentioning

confidence: 99%

“…38 This list of genes was selected from a literature (Pubmed)-based search using the keywords: immunosuppressive cytokines, immunosuppressive mechanisms, chemokines, tumor-supportive myeloid genes, immunosuppressive myeloid and monocyte-related genes, immunosuppressive signaling pathway genes, synthesis of immunosuppressive metabolite, lymphocyte exhaustion marker, lymphocyte inhibitory receptor genes, Tregs genes, tumor immune escape, tumor immune evasion, tumor immune suppression. This search yielded the 54 relevant gene symbols which were selected for the IEGS ( Table 1).…”

Section: Ks Tests For Iegs Distribution Analysismentioning

confidence: 99%

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Several immune escape patterns in non-Hodgkin's lymphomas

et al. 2015

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Follicular Lymphomas (FL) and diffuse large B cell lymphomas (DLBCL) must evolve some immune escape strategy to develop from lymphoid organs, but their immune evasion pathways remain poorly characterized. We investigated this issue by transcriptome data mining and immunohistochemistry (IHC) of FL and DLBCL lymphoma biopsies. A set of genes involved in cancer immune-evasion pathways (Immune Escape Gene Set, IEGS) was defined and the distribution of the expression levels of these genes was compared in FL, DLBCL and normal B cell transcriptomes downloaded from the GEO database. The whole IEGS was significantly upregulated in all the lymphoma samples but not in B cells or other control tissues, as shown by the overexpression of the PD-1, PD-L1, PD-L2 and LAG3 genes. Tissue microarray immunostainings for PD-1, PD-L1, PD-L2 and LAG3 proteins on additional biopsies from 27 FL and 27 DLBCL patients confirmed the expression of these proteins. The immune infiltrates were more abundant in FL than DLBCL samples, and the microenvironment of FL comprised higher rates of PD-1 C lymphocytes. Further, DLBCL tumor cells comprised a higher proportion of PD-1C, PD-L1 C , PD-L2C and LAG3 C lymphoma cells than the FL tumor cells, confirming that DLBCL mount immune escape strategies distinct from FL. In addition, some cases of DLBCL had tumor cells co-expressing both PD-1, PD-L1 and PD-L2. Among the DLBCLs, the activated B cell (ABC) subtype comprised more PD-L1C and PD-L2 C lymphoma cells than the GC subtype. Thus, we infer that FL and DLBCL evolved several pathways of immune escape.

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Section: E1026530-8 Volume 4 Issue 8 Oncoimmunologymentioning

confidence: 99%

Section: Ks Tests For Iegs Distribution Analysismentioning

confidence: 99%

Several immune escape patterns in non-Hodgkin's lymphomas

et al. 2015

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“…These studies revealed distinct phenotypic states or subtypes that stratify gliomas and resemble different glial lineages (1)(2)(3). Although immunological gene expression classifications have been associated with clinical outcomes and prognosis (4,5), precision immunotherapy will ultimately rely on manipulation of the T-cell population that infiltrates gliomas and its underlying repertoire of T-cell receptors (TCRs). However, the structure and intertumoral heterogeneity of the TIL population in gliomas has not been described.…”

mentioning

confidence: 99%

Diversity and divergence of the glioma-infiltrating T-cell receptor repertoire

Sims

Grinshpun

Feng

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

102

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Although immune signaling has emerged as a defining feature of the glioma microenvironment, how the underlying structure of the glioma-infiltrating T-cell population differs from that of the blood from which it originates has been difficult to measure directly in patients. High-throughput sequencing of T-cell receptor (TCR) repertoires (TCRseq) provides a population-wide statistical description of how T cells respond to disease. We have defined immunophenotypes of whole repertoires based on TCRseq of the α-and β-chains from glioma tissue, nonneoplastic brain tissue, and peripheral blood from patients. Using information theory, we partitioned the diversity of these TCR repertoires into that from the distribution of VJ cassette combinations and diversity due to VJ-independent factors, such as selection due to antigen binding. Tumor-infiltrating lymphocytes (TILs) possessed higher VJ-independent diversity than nonneoplastic tissue, stratifying patients according to tumor grade. We found that the VJ-independent components of tumor-associated repertoires diverge more from their corresponding peripheral repertoires than T-cell populations in nonneoplastic brain tissue, particularly for low-grade gliomas. Finally, we identified a "signature" set of TCRs whose use in peripheral blood is associated with patients exhibiting low TIL divergence and is depleted in patients with highly divergent TIL repertoires. This signature is detectable in peripheral blood, and therefore accessible noninvasively. We anticipate that these immunophenotypes will be foundational to monitoring and predicting response to antiglioma vaccines and immunotherapy.T-cell receptor | immunoprofiling | glioma | glioblastoma | immunooncology T he potential for immunotherapy to alleviate progression and recurrence in glioma has inspired intense study of the immunological phenotypes underlying the regulation and selection of tissue-infiltrating lymphocytes (TILs). Motivated by the prospect of targeted therapy, previous studies of glioma have undertaken large-scale genomic and gene expression analysis. These studies revealed distinct phenotypic states or subtypes that stratify gliomas and resemble different glial lineages (1-3). Although immunological gene expression classifications have been associated with clinical outcomes and prognosis (4, 5), precision immunotherapy will ultimately rely on manipulation of the T-cell population that infiltrates gliomas and its underlying repertoire of T-cell receptors (TCRs). However, the structure and intertumoral heterogeneity of the TIL population in gliomas has not been described. Here, we use whole repertoire sequencing of TCRs from glioma tissue and matched peripheral blood to discover novel immunological phenotypes with implications for noninvasive patient monitoring.Local antitumor potential is, in part, a function of the TCR repertoire expressed by T cells that surveil the CNS beyond the bloodbrain barrier. Through somatic V(D)J recombination including random nucleotide insertion in each T-cell, the α-and β-cha...

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“…The involvement of immune cells on glioma progression has been previously described [36][37][38]. Indeed, innate cell immunity and adaptive immune cell response have been implicated in glioblastoma progression [36,37,39,40].…”

Section: Discussionmentioning

confidence: 94%

“…Indeed, innate cell immunity and adaptive immune cell response have been implicated in glioblastoma progression [36,37,39,40]. Interestingly, pathway analysis of the differentially methylated regions comparing initial versus recurrence has pinpointed an enrichment of immune response and mainly macrophage activation (i.e.…”

Section: Discussionmentioning

confidence: 99%

Differential gene methylation in paired glioblastomas suggests a role of immune response pathways in tumor progression

et al. 2015

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DNA and histone methylation are post-transcriptional modifications that have been recently described in gliomas. Indeed, glioma CpG island hypermethylated phenotype has been identified as prognostic biomarker and as a surrogate marker of IDH1/2 mutations. However, the role of DNA methylation in glioblastoma progression is unknown. We sought to analyze DNA methylation levels in paired (initial and recurrent) primary glioblastoma samples to identify candidate pathways that may prone to glioblastoma progression. We have analyzed 12 samples (5 paired samples, two of them with three surgeries) using methylation arrays. We have analyzed differential methylation at probe and at gene region level. Finally, pathway analysis has been performed using differentially methylated regions. All analysis has been performed with R and Bioconductor packages. Mean methylation level at initial sample compared to recurrence was strongly positively correlated (R(2) = 0.98). There was no differentially methylation at probe level. However, at gene level 3080 regions were differentially methylated. Interestingly, pathways analysis showed that the most differentially methylated genes are involved in cellular response to macrophage colony-stimulating factor stimulus (GO:0036006). Methylation levels were strongly conserved when comparing initial to recurrence in primary glioblastomas. Interestingly, differentially methylated pathway analysis suggests that a modulation of methylation in immune response genes may play a role in glioblastoma progression. Further studies are needed to validate the role of methylation of glioblastoma immune response genes in tumor progression.

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Immune Heterogeneity of Glioblastoma Subtypes: Extrapolation from the Cancer Genome Atlas

Cited by 198 publications

References 40 publications

Several immune escape patterns in non-Hodgkin's lymphomas

Several immune escape patterns in non-Hodgkin's lymphomas

Diversity and divergence of the glioma-infiltrating T-cell receptor repertoire

Differential gene methylation in paired glioblastomas suggests a role of immune response pathways in tumor progression

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