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2021 March 29

Sant Pau administers the first CAR-T of its own production for Hodgkin and non-Hodgkin lymphoma T in Europe

The first CAR-T immunotherapy drug produced entirely in Sant Pau (academic) and administered to the first patient is part of a pioneering clinical trial in Europe of CAR-T phase I / II immunotherapy for the autologous treatment of classical Hodgkin lymphoma and relapsed / refractory CD30 + non-Hodgkin T CD30 + lymphoma, funded by the Carlos III Health Institute and the Josep Carreras Leukaemia Foundation.

Recent publications

de Barrios O, Parra M

Epigenetic Control of Infant B Cell Precursor Acute Lymphoblastic Leukemia.

Int J Mol Sci 18 Mar 2021, 22 (6) .
B-cell precursor acute lymphoblastic leukemia (BCP-ALL) is a highly aggressive malignancy, with poorer prognosis in infants than in adults. A genetic signature has been associated with this outcome but, remarkably, leukemogenesis is commonly triggered by genetic alterations of embryonic origin that involve the deregulation of chromatin remodelers. This review considers in depth how the alteration of epigenetic profiles (at DNA and histone levels) induces an aberrant phenotype in B lymphocyte progenitors by modulating the oncogenic drivers and tumor suppressors involved in key cancer hallmarks. DNA methylation patterns have been widely studied in BCP-ALL and their correlation with survival has been established. However, the effect of methylation on histone residues can be very different. For instance, methyltransferase
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Munshi NC, Anderson LD, Shah N, Madduri D, Berdeja J, Lonial S, Raje N, Lin Y, Siegel D, Oriol A, Moreau P, Yakoub-Agha I, Delforge M, Cavo M, Einsele H, Goldschmidt H, Weisel K, Rambaldi A, Reece D, Petrocca F, Massaro M, Connarn JN, Kaiser S, Patel P, Huang L, Campbell TB, Hege K, San-Miguel J

Idecabtagene Vicleucel in Relapsed and Refractory Multiple Myeloma.

N Engl J Med 25 Feb 2021, 384 (8) 705-716.
Background: Idecabtagene vicleucel (ide-cel, also called bb2121), a B-cell maturation antigen-directed chimeric antigen receptor (CAR) T-cell therapy, has shown clinical activity with expected CAR T-cell toxic effects in patients with relapsed and refractory multiple myeloma. Methods: In this phase 2 study, we sought to confirm the efficacy and safety of ide-cel in patients with relapsed and refractory myeloma. Patients with disease after at least three previous regimens including a proteasome inhibitor, an immunomodulatory agent, and an anti-CD38 antibody were enrolled. Patients received ide-cel target doses of 150 × 106 to 450 × 106 CAR-positive (CAR+) T cells. The primary end point was an overall response (partial response or better); a key secondary end point was a complete response or better (comprising complete and stringent complete responses). Results: Of 140 patients enrolled, 128 received ide-cel. At a median follow-up of 13.3 months, 94 of 128 patients (73%) had a response, and 42 of 128 (33%) had a complete response or better. Minimal residual disease (MRD)-negative status (<10-5 nucleated cells) was confirmed in 33 patients, representing 26% of all 128 patients who were treated and 79% of the 42 patients who had a complete response or better. The median progression-free survival was 8.8 months (95% confidence interval, 5.6 to 11.6). Common toxic effects among the 128 treated patients included neutropenia in 117 patients (91%), anemia in 89 (70%), and thrombocytopenia in 81 (63%). Cytokine release syndrome was reported in 107 patients (84%), including 7 (5%) who had events of grade 3 or higher. Neurotoxic effects developed in 23 patients (18%) and were of grade 3 in 4 patients (3%); no neurotoxic effects higher than grade 3 occurred. Cellular kinetic analysis confirmed CAR+ T cells in 29 of 49 patients (59%) at 6 months and 4 of 11 patients (36%) at 12 months after infusion. Conclusions: Ide-cel induced responses in a majority of heavily pretreated patients with refractory and relapsed myeloma; MRD-negative status was achieved in 26% of treated patients. Almost all patients had grade 3 or 4 toxic effects, most commonly hematologic toxic effects and cytokine release syndrome. (Funded by bluebird bio and Celgene, a Bristol-Myers Squibb company; KarMMa ClinicalTrials.gov number, NCT03361748.).
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Pamela Acha, Laura Palomo, Francisco Fuster-Tormo, Bianca Xicoy, Mar Mallo, Ana Manzanares, Javier Grau, Silvia Marcé, Isabel Granada, Marta Rodríguez-Luaces, María Díez-Campelo, Lurdes Zamora, Francesc Solé

Analysis of Intratumoral Heterogeneity in Myelodysplastic Syndromes with Isolated del(5q) Using a Single Cell Approach

Cancers 2021, 13(4), 841 17 Feb 2021, .
Myelodysplastic syndromes (MDS) are a heterogeneous group of hematological diseases. Among them, the most well characterized subtype is MDS with isolated chromosome 5q deletion (MDS del(5q)), which is the only one defined by a cytogenetic abnormality that makes these patients candidates to be treated with lenalidomide. During the last decade, single cell (SC) analysis has emerged as a powerful tool to decipher clonal architecture and to further understand cancer and other diseases at higher resolution level compared to bulk sequencing techniques. In this study, a SC approach was used to analyze intratumoral heterogeneity in four patients with MDS del(5q). Single CD34+CD117+CD45+CD19- bone marrow hematopoietic stem progenitor cells were isolated using the C1 system (Fluidigm) from diagnosis or before receiving any treatment and from available follow-up samples. Selected somatic alterations were further analyzed in SC by high-throughput qPCR (Biomark HD, Fluidigm) using specific TaqMan assays. A median of 175 cells per sample were analyzed. Inferred clonal architectures were relatively simple and either linear or branching. Similar to previous studies based on bulk sequencing to infer clonal architecture, we were able to observe that an ancestral event in one patient can appear as a secondary hit in another one, thus reflecting the high intratumoral heterogeneity in MDS del(5q) and the importance of patient-specific molecular characterization.
Rosalyn W. Sayaman, Mohamad Saad, Vésteinn Thorsson, Donglei Hu, Wouter Hendrickx, Jessica Roelands, Eduard Porta-Pardo, Younes Mokrab, Farshad Farshidfar, Tomas Kirchhoff, Randy F. Sweis, Oliver F. Bathe, Carolina Heimann, Michael J. Campbell, Cynthia Stretch, Scott Huntsman, Rebecca E. Graff, Najeeb Syed, Laszlo Radvanyi, Simon Shelley, Denise Wolf, Francesco M. Marincola, Michele Ceccarelli, Jérôme Galon, Elad Ziv, Davide Bedognetti

Germline genetic contribution to the immune landscape of cancer

Immunity, VOLUME 54, ISSUE 2, P367-386.E8 9 Feb 2021, .
Understanding the contribution of the host’s genetic background to cancer immunity may lead to improved stratification for immunotherapy and to the identification of novel therapeutic targets. We investigated the effect of common and rare germline variants on 139 well-defined immune traits in ∼9000 cancer patients enrolled in TCGA. High heritability was observed for estimates of NK cell and T cell subset infiltration and for interferon signaling. Common variants of IFIH1, TMEM173 (STING1), and TMEM108 were associated with differential interferon signaling and variants mapping to RBL1 correlated with T cell subset abundance. Pathogenic or likely pathogenic variants in BRCA1 and in genes involved in telomere stabilization and Wnt-β-catenin also acted as immune modulators. Our findings provide evidence for the impact of germline genetics on the composition and functional orientation of the tumor immune microenvironment. The curated datasets, variants, and genes identified provide a resource toward further understanding of tumor-immune interactions.
Matteo Bersanelli, Erica Travaglino, Manja Meggendorfer, Tommaso Matteuzzi, Claudia Sala, Ettore Mosca, Chiara Chiereghin, Noemi Di Nanni, Matteo Gnocchi, Matteo Zampini, Marianna Rossi, Giulia Maggioni, Alberto Termanini, Emanuele Angelucci, Massimo Bernardi, Lorenza Borin, Benedetto Bruno, Francesca Bonifazi, Valeria Santini, Andrea Bacigalupo, Maria Teresa Voso, Esther Oliva, Marta Riva, Marta Ubezio, Lucio Morabito, Alessia Campagna, Claudia Saitta, Victor Savevski, Enrico Giampieri, Daniel Remondini, Francesco Passamonti, Fabio Cicer, Niccolò Bolli, Alessandro Rambaldi, Wolfgang Kern, Shahram Kordasti, Francesc Sole, Laura Palomo, Guillermo Sanz, Armando Santoro, Uwe Platzbecker, Pierre Fenaux, Luciano Milanesi, Torsten Haferlach, Gastone Castellani, Matteo G Della Porta

Classification and Personalized Prognostic Assessment on the Basis of Clinical and Genomic Features in Myelodysplastic Syndromes

J Clin Oncol . 2021 Feb 4;JCO2001659. 4 Feb 2021, .
Purpose: Recurrently mutated genes and chromosomal abnormalities have been identified in myelodysplastic syndromes (MDS). We aim to integrate these genomic features into disease classification and prognostication. Methods: We retrospectively enrolled 2,043 patients. Using Bayesian networks and Dirichlet processes, we combined mutations in 47 genes with cytogenetic abnormalities to identify genetic associations and subgroups. Random-effects Cox proportional hazards multistate modeling was used for developing prognostic models. An independent validation on 318 cases was performed. Results: We identify eight MDS groups (clusters) according to specific genomic features. In five groups, dominant genomic features include splicing gene mutations (SF3B1, SRSF2, and U2AF1) that occur early in disease history, determine specific phenotypes, and drive disease evolution. These groups display different prognosis (groups with SF3B1 mutations being associated with better survival). Specific co-mutation patterns account for clinical heterogeneity within SF3B1- and SRSF2-related MDS. MDS with complex karyotype and/or TP53 gene abnormalities and MDS with acute leukemia-like mutations show poorest prognosis. MDS with 5q deletion are clustered into two distinct groups according to the number of mutated genes and/or presence of TP53 mutations. By integrating 63 clinical and genomic variables, we define a novel prognostic model that generates personally tailored predictions of survival. The predicted and observed outcomes correlate well in internal cross-validation and in an independent external cohort. This model substantially improves predictive accuracy of currently available prognostic tools. We have created a Web portal that allows outcome predictions to be generated for user-defined constellations of genomic and clinical features. Conclusion: Genomic landscape in MDS reveals distinct subgroups associated with specific clinical features and discrete patterns of evolution, providing a proof of concept for next-generation disease classification and prognosis.
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