Des méthodes propriétaires et des résultats fiables
L’offre d’AltraBio couvre l’ensemble du flux d’analyse de données de cytométrie en flux, spectrale et de masse, allant du gating automatique à l’identification de biomarqueurs, en passant par le contrôle qualité des données et les analyses de différentiel d’abondance.
Vous souhaitez appliquer votre stratégie de gating sur un grand nombre de fichiers
- 1 à 4 semaines pour générer un automate de gating dédié
- traitement rapide (5-10 min/fichier), 24/7
- Utilisez votre expertise dans le développement de nouvelles stratégies et/ou dans l’interprétation biologique de vos résultats plutôt que dans l’étape de gating
- Nos automates réalisent leurs gating en considérant tous les marqueurs de l’étude. Cela permet d’avoir une meilleure vue sur les populations de cellules que celle qu’on peut avoir en n’utilisant que des biplots.
- Une fois ses performances validées, votre automate de gating sera figé avant d’être utilisé sur tous vos fichiers. Des mises à jour sont toujours possibles mais conduiront à un nouvel automate avec un nouveau numéro de série.
- Grâce à l’automatisation, l’utilisation de la cytométrie dans vos études cliniques, dans lesquelles vous envisagez un grand nombre de fichiers, ne sera plus un problème.
Vous voulez identifier des populations cellulaires marqueurs pour diagnostiquer une maladie ou prédire la réponse à un traitement
Nos solutions validées ont identifié les populations cellulaires pertinentes pour réaliser:
- l’évaluation de la maladie résiduelle mesurable (MRD) dans différents cancers du sang.
- la prediction des patients répondeurs au médicament anti-cancer anti-CTL4 .
- le diagnostic d’une maladie autoimmune.
Notre méthode est capable d’identifier des sous-ensembles de cellules discriminantes à différentes granularités le long d’un axe de différenciation cellulaire, ce qui donne des sous-ensembles de cellules imbriquées : par exemple dans la population de cellules T, les sous-ensembles pertinents peuvent aller du sous-ensemble plus large de cellules CD8 mémoire au plus spécifique. sous-ensemble intégré de la mémoire effectrice CD8.
- Notre approche est moins sensible aux effets de lot.
- Notre méthode peut utiliser des informations supplémentaires telles que les résultats des patients (par exemple, le statut des patients) pour guider intelligemment l’identification des clusters afin d’augmenter encore la pertinence des populations identifiées et d’éviter les faux artefacts.
Vous voulez explorer vos données de cytométrie
- Gating par réduction de dimension : Analyse en composante principale, Minimum Spanning Tree layouts (e.g. SPADE), Multi Dimensional Scaling, t-stochastic neighbor embeddings (e.g. ViSNE), UMAP, etc.
- Clustering: approches basées sur la topologie/le graphe (e.g. SamSPECTRAL), approches basées sur la densité (e.g. Flock), approches basées sur le modèle (e.g. immunoClust, FLAME, FlowClust, flowMerge), approches hybrides (e.g. FlowSOM, Phenograph, FlowPeaks, FlowMeans, etc.), approches d’ensemble, etc.
- Modélisation statistique
- Modèles linéaires généralisés, modèles mixtes (etc) pour (1) l’analyse différentielle d’abondance de populations cellulaires ou (2) l’analyse différentielle de marqueurs d’expression stratifiés par populations cellulaires.
- Machine learning
- Apprentissage supervisé (e.g., Forêt aléatoire, Boosting, SVM, (sparse) PLS), identification de correlation , etc.
- Algorithmes dédiés à des tâches spécifiques
- CITRUS, RchyOptimyx, etc.
Témoignages
« Ils sont très efficaces et agiles, vous n’interagirez pas avec beaucoup de monde donc ils réagissent rapidement et fournissent un service de haute qualité »
“Ils font ce petit contrôle qualité supplémentaire sur leur main, ils vérifient également les transferts, ils mettent cet effort supplémentaire pour s’assurer que ce que nous faisons est exact”
« Le travail que nous faisons jusqu’ici avec AltraBio, c’est du partenariat. … il y avait des échéanciers à respecter et ils sont intervenus et ont dit OK, nous le ferons dans quelques jours, pas dans une semaine, pas dans un mois… quand vous avez cette relation, quand vous comprenez le valeur et vous comprenez les délais du client, cela ressemblait vraiment à un partenariat”
Nos publications en cytometrie
2022
Andrieu, Thibault; Mondière, Paul; Jouve, Pierre-Emmanuel; Dussurgey, Sébastien; Malassigné, Victor; Servanton, Hugo; Baseggio, Lucille; Davi, Frédéric; Michallet, Anne-Sophie; Defrance, Thierry
Mass cytometry analysis reveals attrition of naïve and anergized self-reactive non-malignant B cells in chronic lymphocytic leukemia patients Article de journal
Dans: Front Oncol, vol. 12, p. 1020740, 2022, ISSN: 2234-943X.
@article{pmid36387187,
title = {Mass cytometry analysis reveals attrition of naïve and anergized self-reactive non-malignant B cells in chronic lymphocytic leukemia patients},
author = {Thibault Andrieu and Paul Mondière and Pierre-Emmanuel Jouve and Sébastien Dussurgey and Victor Malassigné and Hugo Servanton and Lucille Baseggio and Frédéric Davi and Anne-Sophie Michallet and Thierry Defrance},
doi = {10.3389/fonc.2022.1020740},
issn = {2234-943X},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
journal = {Front Oncol},
volume = {12},
pages = {1020740},
abstract = {Chronic Lymphocytic Leukemia (CLL) is characterized by the progressive accumulation of monoclonal mature B lymphocytes. Autoimmune complications are common in CLL occurring in up to a quarter of all patients during the course of the illness. Etiology of autoimmunity in CLL is unknown but it is widely admitted that the pathogenic auto-Abs do not originate from the tumoral clone but from the non-malignant B cell pool. This indicates that the developmental scheme of non-malignant B cells could also be perturbed in CLL patients. To address this question, we have designed a B cell-centered antibody panel and used time-of-flight mass cytometry to compare the residual non-malignant B cell pool of CLL patients with the peripheral B cell pool of age-matched healthy donors. We show that the non-malignant B cell compartment of the patients is characterized by profound attrition of naïve B cells and of a population of anergized autoreactive B cells, suggesting impaired B cell lymphopoeisis as well as perturbations of the B cell tolerance checkpoints.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2021
Park, Juliana; Archuleta, Sophia; Oh, May-Lin Helen; Shek, Lynette Pei-Chi; Wang, Hao; Bonaparte, Matthew; Frago, Carina; Bouckenooghe, Alain; Jantet-Blaudez, Frederique; Begue, Sarah; Gimenez-Fourage, Sophie; Pagnon, Anke
Dans: Hum Vaccin Immunother, vol. 17, no. 7, p. 2107–2116, 2021, ISSN: 2164-554X.
@article{pmid33626291,
title = {Humoral and cellular immunogenicity and safety following a booster dose of a tetravalent dengue vaccine 5+ years after completion of the primary series in Singapore: 2-year follow-up of a randomized phase II, placebo-controlled trial},
author = {Juliana Park and Sophia Archuleta and May-Lin Helen Oh and Lynette Pei-Chi Shek and Hao Wang and Matthew Bonaparte and Carina Frago and Alain Bouckenooghe and Frederique Jantet-Blaudez and Sarah Begue and Sophie Gimenez-Fourage and Anke Pagnon},
doi = {10.1080/21645515.2020.1861875},
issn = {2164-554X},
year = {2021},
date = {2021-07-01},
urldate = {2021-07-01},
journal = {Hum Vaccin Immunother},
volume = {17},
number = {7},
pages = {2107--2116},
abstract = {The tetravalent dengue vaccine (CYD-TDV) is approved for use as a 3-dose series for the prevention of dengue in seropositive individuals ≥9 years. A randomized, placebo-controlled, phase II study of a booster dose of CYD-TDV in individuals who completed the 3-dose schedule >5 years previously (NCT02824198), demonstrated that a booster restored neutralizing antibody titers to post-dose 3 levels. We present additional immunogenicity assessments up to 24 months post-booster, and B- and T-cell responses in a participant subset. Participants aged 9-45 years that had received all three doses of CYD-TDV were randomized 3:1 to receive a booster dose of CYD-TDV (n = 89) or placebo (n = 29). Neutralizing antibody levels at Months 1, 6, 12, and 24 post-booster were assessed by plaque reduction neutralization test. In a subset, B-cell responses were assessed by a fluorescent immunospot assay, and T-cells analyzed by flow cytometry at Days 0, 7, 12, Months 1 and 12. We observed an increase of antibody titers Month 1 post-booster, then a gradual decline to Month 24. In the CYD-TDV booster group, an increase in plasmablasts was seen at Day 7 declining by Day 14, an increase in memory B-cells was observed at Day 28 with no persistence at Month 12. CYD-TDV booster recalled a CD8+ T-cell response, dominated by IFN-γ secretion, which decreased 12 months post-booster. This study showed a short-term increase in antibody titers and then gradual decrease following CYD-TDV booster injection >5 years after primary immunization, and the presence of memory B-cells activated following the booster, but with low persistence.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Barturen, Guillermo; Babaei, Sepideh; Català-Moll, Francesc; Martínez-Bueno, Manuel; Makowska, Zuzanna; Martorell-Marugán, Jordi; Carmona-Sáez, Pedro; Toro-Domínguez, Daniel; Carnero-Montoro, Elena; Teruel, María; Kerick, Martin; Acosta-Herrera, Marialbert; Lann, Lucas Le; Jamin, Christophe; Rodríguez-Ubreva, Javier; García-Gómez, Antonio; Kageyama, Jorge; Buttgereit, Anne; Hayat, Sikander; Mueller, Joerg; Lesche, Ralf; Hernandez-Fuentes, Maria; Juarez, Maria; Rowley, Tania; White, Ian; Marañón, Concepción; Anjos, Tania Gomes; Varela, Nieves; Aguilar-Quesada, Rocío; Garrancho, Francisco Javier; López-Berrio, Antonio; Maresca, Manuel Rodriguez; Navarro-Linares, Héctor; Almeida, Isabel; Azevedo, Nancy; Brandão, Mariana; Campar, Ana; Faria, Raquel; Farinha, Fátima; Marinho, António; Neves, Esmeralda; Tavares, Ana; Vasconcelos, Carlos; Trombetta, Elena; Montanelli, Gaia; Vigone, Barbara; Alvarez-Errico, Damiana; Li, Tianlu; Thiagaran, Divya; Alonso, Ricardo Blanco; Martínez, Alfonso Corrales; Genre, Fernanda; Mejías, Raquel López; Gonzalez-Gay, Miguel A; Remuzgo, Sara; Garcia, Begoña Ubilla; Cervera, Ricard; Espinosa, Gerard; Rodríguez-Pintó, Ignasi; Langhe, Ellen De; Cremer, Jonathan; Lories, Rik; Belz, Doreen; Hunzelmann, Nicolas; Baerlecken, Niklas; Kniesch, Katja; Witte, Torsten; Lehner, Michaela; Stummvoll, Georg; Zauner, Michael; Aguirre-Zamorano, Maria Angeles; Barbarroja, Nuria; Castro-Villegas, Maria Carmen; Collantes-Estevez, Eduardo; de Ramon, Enrique; Quintero, Isabel Díaz; Escudero-Contreras, Alejandro; Roldán, María Concepción Fernández; Gómez, Yolanda Jiménez; Moleón, Inmaculada Jiménez; Lopez-Pedrera, Rosario; Ortega-Castro, Rafaela; Ortego, Norberto; Raya, Enrique; Artusi, Carolina; Gerosa, Maria; Meroni, Pier Luigi; Schioppo, Tommaso; Groof, Aurélie De; Ducreux, Julie; Lauwerys, Bernard; Maudoux, Anne-Lise; Cornec, Divi; Devauchelle-Pensec, Valérie; Jousse-Joulin, Sandrine; Jouve, Pierre-Emmanuel; Rouvière, Bénédicte; Saraux, Alain; Simon, Quentin; Alvarez, Montserrat; Chizzolini, Carlo; Dufour, Aleksandra; Wynar, Donatienne; Balog, Attila; Bocskai, Márta; Deák, Magdolna; Dulic, Sonja; Kádár, Gabriella; Kovács, László; Cheng, Qingyu; Gerl, Velia; Hiepe, Falk; Khodadadi, Laleh; Thiel, Silvia; de Rinaldis, Emanuele; Rao, Sambasiva; Benschop, Robert J; Chamberlain, Chris; Dow, Ernst R; Ioannou, Yiannis; Laigle, Laurence; Marovac, Jacqueline; Wojcik, Jerome; Renaudineau, Yves; Borghi, Maria Orietta; Frostegård, Johan; Martín, Javier; Beretta, Lorenzo; Ballestar, Esteban; McDonald, Fiona; Pers, Jacques-Olivier; Alarcón-Riquelme, Marta E
Integrative Analysis Reveals a Molecular Stratification of Systemic Autoimmune Diseases Article de journal
Dans: Arthritis Rheumatol, vol. 73, no. 6, p. 1073–1085, 2021, ISSN: 2326-5205.
@article{pmid33497037,
title = {Integrative Analysis Reveals a Molecular Stratification of Systemic Autoimmune Diseases},
author = {Guillermo Barturen and Sepideh Babaei and Francesc Català-Moll and Manuel Martínez-Bueno and Zuzanna Makowska and Jordi Martorell-Marugán and Pedro Carmona-Sáez and Daniel Toro-Domínguez and Elena Carnero-Montoro and María Teruel and Martin Kerick and Marialbert Acosta-Herrera and Lucas Le Lann and Christophe Jamin and Javier Rodríguez-Ubreva and Antonio García-Gómez and Jorge Kageyama and Anne Buttgereit and Sikander Hayat and Joerg Mueller and Ralf Lesche and Maria Hernandez-Fuentes and Maria Juarez and Tania Rowley and Ian White and Concepción Marañón and Tania Gomes Anjos and Nieves Varela and Rocío Aguilar-Quesada and Francisco Javier Garrancho and Antonio López-Berrio and Manuel Rodriguez Maresca and Héctor Navarro-Linares and Isabel Almeida and Nancy Azevedo and Mariana Brandão and Ana Campar and Raquel Faria and Fátima Farinha and António Marinho and Esmeralda Neves and Ana Tavares and Carlos Vasconcelos and Elena Trombetta and Gaia Montanelli and Barbara Vigone and Damiana Alvarez-Errico and Tianlu Li and Divya Thiagaran and Ricardo Blanco Alonso and Alfonso Corrales Martínez and Fernanda Genre and Raquel López Mejías and Miguel A Gonzalez-Gay and Sara Remuzgo and Begoña Ubilla Garcia and Ricard Cervera and Gerard Espinosa and Ignasi Rodríguez-Pintó and Ellen De Langhe and Jonathan Cremer and Rik Lories and Doreen Belz and Nicolas Hunzelmann and Niklas Baerlecken and Katja Kniesch and Torsten Witte and Michaela Lehner and Georg Stummvoll and Michael Zauner and Maria Angeles Aguirre-Zamorano and Nuria Barbarroja and Maria Carmen Castro-Villegas and Eduardo Collantes-Estevez and Enrique de Ramon and Isabel Díaz Quintero and Alejandro Escudero-Contreras and María Concepción Fernández Roldán and Yolanda Jiménez Gómez and Inmaculada Jiménez Moleón and Rosario Lopez-Pedrera and Rafaela Ortega-Castro and Norberto Ortego and Enrique Raya and Carolina Artusi and Maria Gerosa and Pier Luigi Meroni and Tommaso Schioppo and Aurélie De Groof and Julie Ducreux and Bernard Lauwerys and Anne-Lise Maudoux and Divi Cornec and Valérie Devauchelle-Pensec and Sandrine Jousse-Joulin and Pierre-Emmanuel Jouve and Bénédicte Rouvière and Alain Saraux and Quentin Simon and Montserrat Alvarez and Carlo Chizzolini and Aleksandra Dufour and Donatienne Wynar and Attila Balog and Márta Bocskai and Magdolna Deák and Sonja Dulic and Gabriella Kádár and László Kovács and Qingyu Cheng and Velia Gerl and Falk Hiepe and Laleh Khodadadi and Silvia Thiel and Emanuele de Rinaldis and Sambasiva Rao and Robert J Benschop and Chris Chamberlain and Ernst R Dow and Yiannis Ioannou and Laurence Laigle and Jacqueline Marovac and Jerome Wojcik and Yves Renaudineau and Maria Orietta Borghi and Johan Frostegård and Javier Martín and Lorenzo Beretta and Esteban Ballestar and Fiona McDonald and Jacques-Olivier Pers and Marta E Alarcón-Riquelme},
doi = {10.1002/art.41610},
issn = {2326-5205},
year = {2021},
date = {2021-06-01},
urldate = {2021-06-01},
journal = {Arthritis Rheumatol},
volume = {73},
number = {6},
pages = {1073--1085},
abstract = {OBJECTIVE: Clinical heterogeneity, a hallmark of systemic autoimmune diseases, impedes early diagnosis and effective treatment, issues that may be addressed if patients could be classified into groups defined by molecular pattern. This study was undertaken to identify molecular clusters for reclassifying systemic autoimmune diseases independently of clinical diagnosis.
METHODS: Unsupervised clustering of integrated whole blood transcriptome and methylome cross-sectional data on 955 patients with 7 systemic autoimmune diseases and 267 healthy controls was undertaken. In addition, an inception cohort was prospectively followed up for 6 or 14 months to validate the results and analyze whether or not cluster assignment changed over time.
RESULTS: Four clusters were identified and validated. Three were pathologic, representing "inflammatory," "lymphoid," and "interferon" patterns. Each included all diagnoses and was defined by genetic, clinical, serologic, and cellular features. A fourth cluster with no specific molecular pattern was associated with low disease activity and included healthy controls. A longitudinal and independent inception cohort showed a relapse-remission pattern, where patients remained in their pathologic cluster, moving only to the healthy one, thus showing that the molecular clusters remained stable over time and that single pathogenic molecular signatures characterized each individual patient.
CONCLUSION: Patients with systemic autoimmune diseases can be jointly stratified into 3 stable disease clusters with specific molecular patterns differentiating different molecular disease mechanisms. These results have important implications for future clinical trials and the study of nonresponse to therapy, marking a paradigm shift in our view of systemic autoimmune diseases.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
METHODS: Unsupervised clustering of integrated whole blood transcriptome and methylome cross-sectional data on 955 patients with 7 systemic autoimmune diseases and 267 healthy controls was undertaken. In addition, an inception cohort was prospectively followed up for 6 or 14 months to validate the results and analyze whether or not cluster assignment changed over time.
RESULTS: Four clusters were identified and validated. Three were pathologic, representing "inflammatory," "lymphoid," and "interferon" patterns. Each included all diagnoses and was defined by genetic, clinical, serologic, and cellular features. A fourth cluster with no specific molecular pattern was associated with low disease activity and included healthy controls. A longitudinal and independent inception cohort showed a relapse-remission pattern, where patients remained in their pathologic cluster, moving only to the healthy one, thus showing that the molecular clusters remained stable over time and that single pathogenic molecular signatures characterized each individual patient.
CONCLUSION: Patients with systemic autoimmune diseases can be jointly stratified into 3 stable disease clusters with specific molecular patterns differentiating different molecular disease mechanisms. These results have important implications for future clinical trials and the study of nonresponse to therapy, marking a paradigm shift in our view of systemic autoimmune diseases.