Pheochromocytoma: A genetic and diagnostic update

International audienc

A Combination of CD28 (rs1980422) and IRF5 (rs10488631) Polymorphisms Is Associated with Seropositivity in Rheumatoid Arthritis: A Case Control Study.

INTRODUCTION:The aim of the study was to analyse genetic architecture of RA by utilizing multiparametric statistical methods such as linear discriminant analysis (LDA) and redundancy analysis (RDA). METHODS:A total of 1393 volunteers, 499 patients with RA and 894 healthy controls were included in the study. The presence of shared epitope (SE) in HLA-DRB1 and 11 SNPs (PTPN22 C/T (rs2476601), STAT4 G/T (rs7574865), CTLA4 A/G (rs3087243), TRAF1/C5 A/G (rs3761847), IRF5 T/C (rs10488631), TNFAIP3 C/T (rs5029937), AFF3 A/T (rs11676922), PADI4 C/T (rs2240340), CD28 T/C (rs1980422), CSK G/A (rs34933034) and FCGR3A A/C (rs396991), rheumatoid factor (RF), anti-citrullinated protein antibodies (ACPA) and clinical status was analysed using the LDA and RDA. RESULTS:HLA-DRB1, PTPN22, STAT4, IRF5 and PADI4 significantly discriminated between RA patients and healthy controls in LDA. The correlation between RA diagnosis and the explanatory variables in the model was 0.328 (Trace = 0.107; F = 13.715; P = 0.0002). The risk variants of IRF5 and CD28 genes were found to be common determinants for seropositivity in RDA, while positivity of RF alone was associated with the CTLA4 risk variant in heterozygous form. The correlation between serologic status and genetic determinants on the 1st ordinal axis was 0.468, and 0.145 on the 2nd one (Trace = 0.179; F = 6.135; P = 0.001). The risk alleles in AFF3 gene together with the presence of ACPA were associated with higher clinical severity of RA. CONCLUSIONS:The association among multiple risk variants related to T cell receptor signalling with seropositivity may play an important role in distinct clinical phenotypes of RA. Our study demonstrates that multiparametric analyses represent a powerful tool for investigation of mutual relationships of potential risk factors in complex diseases such as RA

The Significant Reduction or Complete Eradication of Subcutaneous and Metastatic Lesions in a Pheochromocytoma Mouse Model after Immunotherapy Using Mannan-BAM, TLR Ligands, and Anti-CD40

Therapeutic options for metastatic pheochromocytoma/paraganglioma (PHEO/PGL) are limited. Here, we tested an immunotherapeutic approach based on intratumoral injections of mannan-BAM with toll-like receptor ligands into subcutaneous PHEO in a mouse model. This therapy elicited a strong innate immunity-mediated antitumor response and resulted in a significantly lower PHEO volume compared to the phosphate buffered saline (PBS)-treated group and in a significant improvement in mice survival. The cytotoxic effect of neutrophils, as innate immune cells predominantly infiltrating treated tumors, was verified in vitro. Moreover, the combination of mannan-BAM and toll-like receptor ligands with agonistic anti-CD40 was associated with increased mice survival. Subsequent tumor re-challenge also supported adaptive immunity activation, reflected primarily by long-term tumor-specific memory. These results were further verified in metastatic PHEO, where the intratumoral injections of mannan-BAM, toll-like receptor ligands, and anti-CD40 into subcutaneous tumors resulted in significantly less intense bioluminescence signals of liver metastatic lesions induced by tail vein injection compared to the PBS-treated group. Subsequent experiments focusing on the depletion of T cell subpopulations confirmed the crucial role of CD8+ T cells in inhibition of bioluminescence signal intensity of liver metastatic lesions. These data call for a new therapeutic approach in patients with metastatic PHEO/PGL using immunotherapy that initially activates innate immunity followed by an adaptive immune response

Hypoxia-Inducible Factor 2α Mutation-Related Paragangliomas Classify as Discrete Pseudohypoxic Subcluster

Recently, activating mutations of the hypoxia-inducible factor 2α gene (HIF2A/EPAS1) have been recognized to predispose to multiple paragangliomas (PGLs) and duodenal somatostatinomas associated with polycythemia, and ocular abnormalities. Previously, mutations in the SDHA/B/C/D, SDHAF2, VHL, FH, PHD1, and PHD2 genes have been associated with HIF activation and the development of pseudohypoxic (cluster-1) PGLs. These tumors overlap in terms of tumor location, syndromic presentation, and noradrenergic phenotype to a certain extent. However, they also differ especially by clinical outcome and by presence of other tumors or abnormalities. In the present study, we aimed to establish additional molecular differences between HIF2A and non-HIF2A pseudohypoxic PGLs. RNA expression patterns of HIF2A PGLs (n = 6) from 2 patients were compared with normal adrenal medullas (n = 8) and other hereditary pseudohypoxic PGLs (VHL: n = 13, SDHB: n = 15, and SDHD: n = 14). Unsupervised hierarchical clustering showed that HIF2A PGLs made up a separate cluster from other pseudohypoxic PGLs. Significance analysis of microarray yielded 875 differentially expressed genes between HIF2A and other pseudohypoxic PGLs after normalization to adrenal medulla (false discovery rate 0.01). Prediction analysis of microarray allowed correct classification of all HIF2A samples based on as little as three genes (TRHDE, LRRC63, IGSF10; error rate: 0.02). Genes with the highest expression difference between normal medulla and HIF2A PGLs were selected for confirmatory quantitative reverse transcriptase polymerase chain reaction. In conclusion, HIF2A PGLs show a characteristic expression signature that separates them from non-HIF2A pseudohypoxic PGLs. Unexpectedly, the most significantly differentially expressed genes have not been previously described as HIF target genes

The genetic discrimination of RA patients and controls.

<p>Linear discrimination analysis diagram shows that shared epitope and single nucleotide polymorphisms in PTPN22, STAT4, IRF5 and PADI4 genes significantly discriminated between RA patients and healthy controls. RA—RA patients; C—control group; SE (0,1,2)—number of SE coding allele in HLA-DRB1 gene (✧); IRF5 (CC, CT, TT)—genotypes in IRF5 gene (C risk allele) (◁); PADI4 (TT, CT, CC)–genotypes in PADI4 gene (T risk allele) (▽); PTPN22 (CC, CT, TT)–genotypes in PTPN22 gene (A risk allele) (△); STAT4 (GG, GT, TT)–genotypes in STAT4 gene (T risk allele) (☐). Diagram reading clue: Small circles represent individual cases. Large grey circles—centroids—represent subject groups (RA patients and controls). Symbols are genetic factors. Large bold symbols represent genotypes significantly influencing the distribution of subjects. Small empty symbols represent other genotypes of selected genes. The closer to the group centroid the gene symbol lies, the stronger is its impact on the classification of subjects to particular group.</p

SNPs associated with seropositivity in RA.

<p>Redundancy discrimination analysis plot showing that IRF5, CD28 and CTLA4 are associated with seropositivity in RA patients. RF+–rheumatoid factor positive RA patients; RF-–rheumatoid factor negative RA patients; ACPA+–anti-citrullinated peptides antibodies positive RA patients; ACPA-–anti-citrullinated peptides antibodies negative RA patients; SE (0,1,2)—number of shared epitope coding alleles in HLA-DRB1 gene (✧); IRF5 (CC, CT, TT)—genotypes in IRF5 gene (C risk allele) (▷); CD28 (CC, CT, TT)–genotypes in CD28 gene (C risk allele) (◁); CTLA4 (AG, GG, AA)–genotypes in CTLA4 gene (G risk allele) (◊). Diagram reading clue: Symbols are genetic factors. Large bold symbols represent genotypes significantly influencing the presence of RF and ACPA. Small empty symbols represent other genotypes of selected genes. Direction of arrow indicates which serologic status is associated with the genetic parameters and the length of the arrow indicates the magnitude of the association.</p

Basic demographics of RA cases and healthy controls.

<p>Basic demographics of RA cases and healthy controls.</p