BackgroundThe search for immunological markers with ability of predicting clinical outcome is a priority in lymphomas, and in cancer in general. It is well known that some immunomodulatory cells, such as myeloid derived suppressor cells (MDSCs) or regulatory T cells (Tregs), are recruited by tumors, jeopardizing antitumor immunosurveillance. In this work, we have studied blood levels of these immunosuppressive cells in patients with relapsed/refractory diffuse large B-cell lymphoma (R/R DLBCL), prior to and along the course of the experimental rituximab, gemcitabine, dexamethasone, and cisplatin (R2-GDP) schedule, as a translational substudy of the R2-GDP-GOTEL trial (EudraCT Number: 2014-001620-29), which included lenalidomide as an immunomodulator.MethodsBlood samples were taken before treatment, at cycle 3 and end of induction. Samples were analyzed by flow cytometry. Non-parametric tests were used. Mann-Whitney U test was used to compare basal cells distributions, and Wilcoxon test was considered to compare cells distribution at different times. Spearman test was performed to measure the degree of association between cell populations.ResultsIn this study, MDSC and Treg circulating concentration was found increased in all patients compared with a healthy control group and decreased after treatment only in patients with longest overall survival (>24 months), reaching the levels of the healthy group. Likewise, the number of inhibited T lymphocytes expressing Programmed Death-1 (PD-1) were increased in peripheral blood from patients and decreased on the treatment, whereas activated T lymphocytes increased after therapy in those with better overall survival.ConclusionsIn conclusion, blood concentration of MDSCs and Treg cells may be good prognostic markers for overall survival after 2 years in R/R DLBCL. These results point to a possible role of these elements in the immunosuppression of these patients, as assessed by the circulating activated and inhibited T lymphocytes, and therefore, they may be considered as therapeutic targets in DLBCL.

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Background: Urachal carcinoma (UrC) represents < 1 % of bladder carcinomas and is developed from an embryonic remnant connecting to the umbilicus. Because of its rarity, the standard of care is not well defined. Methods:We identified patients (pts) treated for UrC by the GETUG-AFU group. Data were collected retrospectively and analyzed for pts characteristics and outcomes.Background: Seventy percent of testicular non-seminomatous germ cell tumors (NSGCT) are cured with only orchiectomy, so the adjuvant treatment is an overtreatment in most patients. The objective of the study was to find a gene expression model that would help us select the patients with the highest risk of relapse.Methods: Retrospective study of 54 patients with stage I NSGCT without adjuvant treatment (48% with relapse and 52% without relapse). Gene expression differences were analyzed using the PanCancer panel. Bioinformatics tools were used to find a gene expression signature, based on the selection of embedded type characteristics, using nine classification models (Lasso, Ridge, Gradient Boosting, Random Forest, ExtraTrees, LogisticRegression, SGDC, Passive Aggressive Classifier and SVR).Results: A nine gene model (MPL, Col24a1, NR4A1, FOSL1, CREB5, FANCB, LAMB4, ZBTB16, CALML3) was obtained with the ability to predict the risk of relapse in patients with NSGCT stage I without adjuvant treatment, AUC 0.8. Of these genes, four are related to the PI3K signaling pathway (Col24a1, NR4A1, CREB5, LAMB4). From the nine gene model highlights FOSL1, with a correlation with relapse of 0.43, and NR4A1 abstracts Annals of Oncology Volume 31 -Issue S4 -2020 S601and ZBTB16, with a differential expression close to statistical significance (0.075 in both cases). Conclusions:In stage I NSGCT treated with only orchiectomy a differential gene expression signature of nine genes has been identified (MPL, Col24a1, NR4A1, FOSL1, CREB5, FANCB, LAMB4, ZBTB16, CALML3) that allows selecting those patients with a high risk of relapse, although these data need validation in a larger population of patients.