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. 2013 Oct 1;8(10):e74798.
doi: 10.1371/journal.pone.0074798. eCollection 2013.

Association between inflammatory infiltrates and isolated monosomy 22/del(22q) in meningiomas

Patrícia Henriques Domingues  1 , Cristina Teodósio, Álvaro Otero, Pablo Sousa, Javier Ortiz, María del Carmen García Macias, Jesús María Gonçalves, Ana Belén Nieto, María Celeste Lopes, Catarina de Oliveira, Alberto Orfao, Maria Dolores Tabernero
Affiliations

Association between inflammatory infiltrates and isolated monosomy 22/del(22q) in meningiomas

Patrícia Henriques Domingues et al. PLoS One. .

Abstract

Meningiomas contain highly variable levels of infiltrating tissue macrophages (TiMa) and other immune cells. In this study we investigated the potential association between the number and immunophenotype of inflammatory and other immune cells infiltrating the tumor as evaluated by multiparameter flow cytometry, and the clinico-biological, cytogenetic and gene expression profile (GEP) of 75 meningioma patients. Overall, our results showed a close association between the amount and cellular composition of the inflammatory and other immune cell infiltrates and the cytogenetic profile of the tumors. Notably, tumors with isolated monosomy 22/del(22q) showed greater numbers of TiMa, NK cells and (recently)-activated CD69(+) lymphocytes versus meningiomas with diploid and complex karyotypes. In addition, in the former cytogenetic subgroup of meningiomas, tumor-infiltrating TiMa also showed a more activated and functionally mature phenotype, as reflected by a greater fraction of CD69(+), CD63(+), CD16(+) and CD33(+) cells. GEP at the mRNA level showed a unique GEP among meningiomas with an isolated monosomy 22/del(22q) versus all other cases, which consisted of increased expression of genes involved in inflammatory/immune response, associated with an M1 TiMa phenotype. Altogether, these results suggest that loss of expression of specific genes coded in chromosome 22 (e.g. MIF) is closely associated with an increased homing and potentially also anti-tumoral effect of TiMa, which could contribute to explain the better outcome of this specific good-prognosis cytogenetic subgroup of meningiomas.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Immunohistochemical staining of meningioma tissues with the anti-CD68 antibody.
CD68-positive cells detected within the tumor parenchyma showed reactivity in their cytoplasm and a mononuclear cell appearance, compatible with macrophages infiltrating the tumor. An overview of the whole tissue from a representative case (original magnification, ×400) (panel A) and a higher amplification of areas containing CD68-positive cells (original magnification, ×1000) (panel B), are displayed.
Figure 2
Figure 2. Distribution of tumor cells, inflammatory and other immune cells in meningioma samples classified according to the cytogenetic profile of the tumor.
Percentage of tumor cells (panel A), tissue macrophages (TiMa) (panel B) and total lymphocytes infiltrating meningioma samples (panel C), grouped according to the cytogenetic iFISH profile of the tumor, are shown, as also the ratio between the number of tumor cells and all other infiltrating cells (panel D). Notched-boxes represent 25th and 75th percentile values; the lines in the middle and vertical lines correspond to median values and the 10th and 90th percentiles, respectively.
Figure 3
Figure 3. Immunophenotype of Tissue macrophages (TiMa) infiltrating meningioma samples, according to the cytogenetic profile of tumor cells.
The percentage of TiMa expressing CD69 (panel A), CD63 (panel B), CD16 (panel C) and CD33 (panel D) are shown together with the mean amount of CD44 (panel E) and CD9 (panel F) expressed per TiMa infiltrating meningioma samples, according to the iFISH profile of tumor cells. MFI, mean fluorescence intensity (arbitrary fluorescence units) per cell. Notched-boxes represent 25th and 75th percentile values; the lines in the middle and vertical lines correspond to median values and the 10th and 90th percentiles, respectively.
Figure 4
Figure 4. Distribution of the major lymphocyte subsets and activated CD69+ lymphocytes in inflammatory infiltrates of meningiomas classified according to the cytogenetic profile of tumor cells.
The percentage of total CD3+ T cells (panel A), CD3+ CD8− T cells (panel B), CD3+ CD8+ T cells (panel C), activated CD69+ lymphocytes (panel D), CD3− CD19− 56+ NK cells (panel E) and CD3− CD19+ B cells (panel F) are shown. Notched-boxes represent 25th and 75th percentile values; the lines in the middle and vertical lines correspond to median values and the 10th and 90th percentiles, respectively.
Figure 5
Figure 5. Hierarchical clustering analysis of meningioma samples based on the relative distribution and the activation-associated (CD69+) immunophenotypic profile of infiltrating inflammatory cells and lymphocytes: relationship with the cytogenetic subgroups of the disease.
Results are presented in a matrix format where each column represents a single immunophenotypic variable and each row corresponds to a different meningioma sample (rows annotated as ‘D’, ‘−22’ and ‘C’ correspond to meningiomas with diploid, isolated monosomy 22/del(22q) and complex iFISH karyotypes, respectively). Normalized values are represented by a color scale where red and green colors reflect values above and below the mean values obtained for each variable, respectively (panel A). A 3-dimensional principal component analysis (PCA) representation of all meningioma samples based on the number and features of inflammatory cells and lymphocytes infiltrating the tumor, as analyzed by flow cytometry (n = 51) is displayed; as shown there, most tumors with isolated monosomy 22/del(22q) (orange dots) tend to cluster together based on the pattern of infiltration of the tumor by inflammatory and other immune cells (panel B).
Figure 6
Figure 6. Hierarchical clustering analysis of the GEP of meningioma samples.
Results are presented in a GEP matrix format where each row represents a single gene (listed with the corresponding gene symbol) and each column corresponds to a distinct meningioma sample (n = 40); those columns identified as ‘D’ (colored yellow), ‘−22’ (colored orange) and ‘C’ (blue color) correspond to individual meningioma tumors with a diploid, monosomy 22/del(22q) and complex iFISH karyotype, respectively. Normalized values are represented by a color scale where red and green colors indicate values above and below the mean mRNA expression values, respectively. Hierarchical clustering analysis was based on the expression of those 79 genes which showed the highest classification power for the three cytogenetic subgroups of meningiomas. On the right side of the plot, the major common functions of the listed genes, based on the analyses performed with the Ingenuity Pathway software, are indicated. As displayed, genes overexpressed in meningiomas carrying monosomy 22/del(22q) are mainly involved in inflammatory cell functions.
Figure 7
Figure 7. Schematic representation of the functional impact of GEP of meningiomas with isolated monosomy 22/del(22q).
The scheme was built based on the results obtained through the analysis of GEP performed with the Ingenuity Pathway Analysis software and it shows increased expression of several inflammatory genes, particularly genes involved in antigen presenting cell functions, among cases with isolated monosomy 22/del(22q). Such genes include HLA and HLA-associated molecules (HLA-DMA, HLA-DMB, HLA-DRA, HLA-DRB1, HLA-DQA1, HLA-DQB and CD74), cytokines (IL16, IL1B, IL1R1, IL10RA, IL11RA and IL17RA), growth factors and growth factor receptors (CSF1, CSF1R, IGF1, IGF2R, VEGF and PDGFRB), complement proteins (C5, C3, C3AR1, C5AR1 and CD59), immunoglobulin Fc (FcIg) receptors (FCGR1A, FCGR2A, FCGR3B and FCER1G) and the CCR1 chemokine receptor, integrins (ITGAM, ITGAX, ITGA4 and ITGB2) and other adhesion molecules (VCAM1, CD44, CD53, CD58, CD81 and CD93), immune co-stimulatory molecules (CD4, CD40 and CD86), toll-like receptors (TLR2, TLR5 and TLR7) and TLR-associated molecules (CD14 and MYD88), together with phosphoinositide-3-kinases (PIK3CG and PIK3CD) and other kinases (PRKCA, PRKCD, SYK, LYN and HCK), tyrosine phosphatases (PTPRC and PTPN6), and apoptotic proteins (BCL2 and BID), together with other signaling molecules (CD69, CYBB, GAB2, HIF1A, INPP5D, IRF5, IRF8, MIF, MSR1, SEMA4D, TREM2, TYROBP and WAS).
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Grants and funding

This work was partially supported by grants from the Fundação para a Ciência e Tecnologia (PIC/IC/83108/2007, FCT, Portugal), Fondo de Investigaciones Sanitarias (FIS/FEDER 06/0312 and RETICC RD06/0020/0035, Instituto de Salud Carlos III, Ministerio de Sanidad y Consumo, Madrid, Spain), Caja Burgos (Spain), and Fundación MMA (exp 75312010 and 87692011, Madrid, Spain). Patrícia Domingues is supported by grant (SFRH/BD/64799/2009) from FCT. Maria Dolores Tabernero is supported by IECSCYL (Soria, Spain). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.