1. The production of increased ketonemia by either growth hormone or adrenocorticotropic hormone in fasted normal rats is confirmed. 2. Under the experimental conditions used, the degree of ketonemia produced is correlated with the amount of hormone administered.
Association of Hodgkin lymphoma and non-Hodgkin lymphoma is rare and, specifically, the combination of Hodgkin lymphoma and mantle cell lymphoma has not been previously described. Here we describe composite mantle cell lymphoma and Hodgkin lymphoma affecting the spleen in one case and the eyelid and cervical lymph nodes in a second. In both, nodules of classical Hodgkin lymphoma were intermixed with diffuse or nodular areas of typical mantle cell lymphoma. Immunohistochemical and molecular analyses confirmed cyclin D1 overexpression secondary to the translocation t(11;14) in the small mantle cell lymphoma component; with CD30, CD15, and EBV expression in the Hodgkin and Reed-Sternberg cells. Finally, clonal analysis of rearranged immunoglobulin genes performed on microdissected Hodgkin and Reed-Sternberg and mantle cell lymphoma cells provided definite evidence of separate clonal origins of the two tumors in the patients. These EBV-positive, clonally unrelated tumors seem to represent true composite neoplasms, in contrast to cases showing merely clonal progression.
Mycosis fungoides (MF) and Sézary syndrome (SS) are the most common subtypes of cutaneous T-cell lymphomas. The diagnosis of these patients is very challenging and requires an integrated approach, incorporating clinical, morphological, immunophenotypic and molecular features. The molecular substrate of early and advanced stages of MF / SS is still poorly understood and, consequently, treatment selection is mainly based on clinical data. The study aimed to transfer what is known about the molecular pathogenesis of MF / SS to early diagnosis, prognosis, and selection of therapy by identifying molecular markers associated with the course of the disease. Using the NanoString platform for gene-expression analysis, we design a custom panel of 77 genes relevant in the pathogenesis of MF/SS, together with genes known to be therapeutic targets. A series of 81 formalin-fixed, paraffin-embedded (FFPE) samples belonging to 27 MF/SS patients in different phases of the disease are included in the study. The technique was informative in all analyzed cases, independently of the clinical or histological stage or density of the tumor infiltration. For each case or sample the analysis provided an objective measure of the T-cell phenotype (T-cell differentiation gene sets), cellular composition of the infiltrate (dendritic cells, macrophages, B-cells,…) expression of markers used for therapy selection (CD30, CXCR4 and KIR3DL2) and expression level of surrogate markers for the main cell-survival oncogenic pathways. Unexpectedly, non-supervised clustering showed that most of the clustering was dependent of the patient identity, suggesting that MF/SS has a high degree of inter-tumoral heterogeneity and that molecular signature for each patient tends to remain relatively stable along the disease. Samples corresponding to pre-MF lesions tend to cluster with early MF/SS samples, suggesting that pre-MF lesions indeed correspond to early phases of the disease. On the other hand, patients who progress to advanced stages have a tendency to cluster with each other. Several differentially expressed genes were comparing early and advanced stages. FGFR3, NUAK1, FJX1, CXCL12 and RORC were up regulated in early lesions, while CARD11, CD2, CD38, CD3D, CD3E, CD3G, CXCR4, GZMA, IL10 and SELL were up - regulated in tumors (p< 0,005). Gene-expression profiling using a customized NanoString platform can be applied to routine paraffin embedded MF/SS samples and provides data that allow to a better understanding of MF genesis and progression. MF/SS samples show an unexpected high degree of inter-tumoral heterogeneity, suggesting that every patient has some individual molecular signature features that are found in consecutive biopsies. The analysis brings also particular gene signatures associated with early MF and progression, allowing recognizing stage-specific signatures. EA - previously submitted to regional or national meetings (up to 1000 attendees) The research was funded by: The research was supported by grants from Instituto de Salud Carlos III, from Ministerio de Economía, Industria y Competitividad, Asociación Española Contra el Cáncer (AECC), Comunidad Autónoma de Madrid and Centro de Investigación Biomédica en Red de Cáncer (CIBERONC): SAF2013-47416-R, CIBERONC-ISCIII, ISCIII-MINECO-AES-FEDER (Plan Estatal I + D + I 2013-2016), AECC PROYE18054PIRI, CAM B2017/BMD-3778, PIC97/2017_FJD, PIE15/0081, PIE16/01294 and PIE19/00715. L.Tomas-Roca was funded by Marie Skłodowska-Curie Individual Fellowship (No 882597) Conflicts of interests pertinent to the abstract Consultant or advisory role Millenium/Takeda. Celgene. Gilead. Jansen. Nanostring. Kyowa Kirin Research funding: Millenium/Takeda. Gilead. Kura
Introduction: Peripheral T-cell Lymphomas (PTCLs) are aggressive tumours with unfavourable prognosis, with around 30% overall survival (OS) after 5 years. Histological and molecular studies have revealed a striking degree of heterogeneity, with three major PTCL subtypes defined. Consistent diagnosis and prognostication are still difficult to achieve, because of the difficulty of reproducing results, and the dearth of clinically applicable prognostic biological markers. Methods: We have analyzed a series of 105 PTCL cases (66 angioimmunoblastic T-cell lymphoma, AITL; 21 PTCL-not otherwise specified, PTCL-NOS; and 18 PTCL-with T follicular helper phenotype, PTCL-TFH) patients using a customized NanoString platform that includes 208 genes associated with T-cell differentiation, oncogenes and tumor suppressor genes, deregulated pathways and stromal cell subpopulations. Specifically, the platform includes genes expressed by the multiple cell types present in PTCL specimens, together with normal T-cell populations. These are used to try and enable the deconvolution of the T-cell lymphoma microenvironment, and thereby develop an integrated perspective on the cell composition of PTCL tumor specimens. Results: A comparative analysis of the various histological types of PTCL (AITL, PTCL-NOS and PTCL-TFH) showed specific sets of genes to be associated with each of the diagnoses, including TFH markers, cytotoxic markers and genes whose expression was a surrogate for specific cellular subpopulations, including follicular dendritic cells, mast cells and genes belonging to specific cell-survival pathways (NF-κB). Unsupervised analysis of the expression of the genes here studied revealed clusters of co-regulated genes that identified the main cell components of the tumor. The analysis did not reveal any differences in survival probability associated with the histological sub-classification, but did identify specific genes and gene sets whose expression was associated with changes in survival probability for each of the PTCL subtypes, independently of the clinical variables included in the International Prognostic Index (IPI). These included a B-cell gene set in cases of AITL, the expression of proliferation markers in PTCL-NOS, and the expression of cytotoxic markers in cases with a diagnosis of PTCL-TFH. For each PTCL lymphoma type, a multivariate analysis identified genes that allow the series of cases to be stratified into different risk groups. This was validated for AITL in an independent series of 54 additional cases. Conclusions: In summary, our study supports the current division of PTCL into these three categories (AITL, PTCL-NOS and PTCL-TFH), identifies gene sets potentially useful for this classification and recognizes the expression of B-cell genes as an IPI-independent prognostic factor for AITL subtype. EA – previously submitted to regional or national meetings (up to 1000 attendees). The research was funded by: The research was supported by grants from Instituto de Salud Carlos III, from Ministerio de Economía, Industria y Competitividad, Asociación Española Contra el Cáncer (AECC), Comunidad Autónoma de Madrid and Centre for Biomedical Network Research on Cancer (CIBERONC): SAF2013-47416-R, CIBERONC-ISCIII (CB16/12/00291), ISCIII-MINECO-AES-FEDER (Plan Estatal I + D + I 2013-2016), ISCIII-MINECO AES-FEDER (Plan Estatal I + D + I 2017-2020), AECC PROYE18054PIRI, CAM B2017/BMD-3778, PIC97/2017_FJD, PIE15/0081, PI17/00272, PIE16/01294, GILEAD (GL18/00019) and PIC 041-19. L. Tomas-Roca was funded by Marie Skłodowska-Curie Individual Fellowship (No 882597). Keywords: Genomics, Epigenomics, and Other -Omics, Diagnostic and Prognostic Biomarkers, Aggressive T-cell non-Hodgkin lymphoma Conflicts of interests pertinent to the abstract M. Án. Piris Consultant or advisory role: Millenium/Takeda, Celgene, Gilead, Jansen, NanoString, Kyowa Kirin Research funding: Millenium/Takeda, Gilead, Kura
The majority of meningiomas are probably benign but a number of tumors display considerable histological and/ or clinical aggressivity, sometimes with unexpectedly high recurrence rates after radical removal.Understanding the potential behavior of these tumors in individual patients is critical for rational therapeutic decision-making.This study aimed to identify gene expression profiles and candidate markers associated with original and recurrent meningiomas.Unsupervised hierarchical clustering of the samples confirmed 2 main groups of meningiomas with distinct clinical behaviors.The gene expression profiling study identified genes and pathways potentially associated with meningioma recurrence, revealing an overall lower level of gene expression.The differential gene expression profiling analyses of original and recurrent meningiomas identified 425 known genes and expressed sequence tags related to meningioma recurrence, with SFRP1 (8p12), TMEM30B (14q23), and CTGF (6q23) showing the most disparate expression.Most of the differentially expressed genes were located at 1p, 6q, and 14q and were underexpressed in recurrences.Loss of such chromosomal regions has previously been associated with a higher risk of meningioma recurrence or malignant progression.Thus, at these locations, we propose the existence of novel candidate genes that could be involved in meningioma recurrence.In addition, the overexpression of genes of histone cluster 1 (6p) in recurrent meningiomas is reported here for the first time.Finally, the altered genes related to meningioma recurrence are involved in pathways such as Notch, TGFb, and Wnt, as described previously, and in other pathways such as cell cycle, oxidative phosphorylation, PPAR, and PDGF, not related before to meningioma recurrence.
Abstract Purpose: Despite major advances in the treatment of classic Hodgkin's lymphoma (cHL), ∼30% of patients in advanced stages may eventually die as result of the disease, and current methods to predict prognosis are rather unreliable. Thus, the application of robust techniques for the identification of biomarkers associated with treatment response is essential if new predictive tools are to be developed. Experimental Design: We used gene expression data from advanced cHL patients to identify transcriptional patterns from the tumoral cells and their nonneoplastic microenvironment, associated with lack of maintained treatment response. Gene-Set Enrichment Analysis was used to identify functional pathways associated with unfavorable outcome that were significantly enriched in either the Hodgkin's and Reed-Sternberg cells (regulation of the G2-M checkpoint, chaperones, histone modification, and signaling pathways) or the reactive cell microenvironment (mainly represented by specific T-cell populations and macrophage activation markers). Results: To explore the pathways identified previously, we used a series of 52 formalin-fixed paraffin-embedded advanced cHL samples and designed a real-time PCR-based low-density array that included the most relevant genes. A large majority of the samples (82.7%) and all selected genes were analyzed successfully with this approach. Conclusions: The results of this assay can be combined in a single risk score integrating these biological pathways associated with treatment response and eventually used in a larger series to develop a new molecular outcome predictor for advanced cHL.