Publications

@article{pmid39270324,

title = {Trem2-expressing multinucleated giant macrophages are a biomarker of good prognosis in head and neck squamous cell carcinoma},

author = {Gregoire Gessain and Ahmed-Amine Anzali and Marvin Lerousseau and Kevin Mulder and Mathilde Bied and Anne Auperin and Daniel Stockholm and Nicolas Signolle and Farah Sassi and Maria Eugenia Marques Da Costa and Antonin Marchais and Alexandre Sayadi and Daniela Weidner and Stefan Uderhardt and Quentin Blampey and Sumanth Reddy Nakkireddy and Sophie Broutin and Charles-Antoine Dutertre and Pierre Busson and Thomas Walter and Alix Marhic and Antoine Moya-Plana and Joanne Guerlain and Ingrid Breuskin and Odile Casiraghi and Philippe Gorphe and Marion Classe and Jean-Yves Scoazec and Camille Bleriot and Florent Ginhoux},

doi = {10.1158/2159-8290.CD-24-0018},

issn = {2159-8290},

year  = {2024},

date = {2024-09-01},

journal = {Cancer Discov},

abstract = {Patients with head and neck squamous cell carcinomas (HNSCC) often have poor outcomes due to suboptimal risk-management and treatment strategies; yet integrating novel prognostic biomarkers into clinical practice is challenging. Here, we report the presence of multinucleated giant cells (MGC) - a type of macrophages - in tumors from patients with HNSCC, which are associated with a favorable prognosis in treatment-naive and preoperative-chemotherapy-treated patients. Importantly, MGC density increased in tumors following preoperative therapy, suggesting a role of these cells in the anti-tumoral response. To enable clinical translation of MGC density as a prognostic marker, we developed a deep-learning model to automate its quantification on routinely stained pathological whole slide images. Finally, we used spatial transcriptomic and proteomic approaches to describe the MGC-related tumor microenvironment and observed an increase in central memory CD4 T cells. We defined an MGC-specific signature resembling to TREM2-expressing mononuclear tumor associated macrophages, which co-localized in keratin tumor niches.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38915885,

title = {CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data},

author = {Corentin Thuilliez and Gaël Moquin-Beaudry and Pierre Khneisser and Maria Eugenia Marques Da Costa and Slim Karkar and Hanane Boudhouche and Damien Drubay and Baptiste Audinot and Birgit Geoerger and Jean-Yves Scoazec and Nathalie Gaspar and Antonin Marchais},

doi = {10.1093/bioadv/vbae081},

issn = {2635-0041},

year  = {2024},

date = {2024-01-01},

journal = {Bioinform Adv},

volume = {4},

number = {1},

pages = {vbae081},

abstract = {MOTIVATION: Spatial transcriptomics enables the analysis of cell crosstalk in healthy and diseased organs by capturing the transcriptomic profiles of millions of cells within their spatial contexts. However, spatial transcriptomics approaches also raise new computational challenges for the multidimensional data analysis associated with spatial coordinates.nnRESULTS: In this context, we introduce a novel analytical framework called CellsFromSpace based on independent component analysis (ICA), which allows users to analyze various commercially available technologies without relying on a single-cell reference dataset. The ICA approach deployed in CellsFromSpace decomposes spatial transcriptomics data into interpretable components associated with distinct cell types or activities. ICA also enables noise or artifact reduction and subset analysis of cell types of interest through component selection. We demonstrate the flexibility and performance of CellsFromSpace using real-world samples to demonstrate ICA's ability to successfully identify spatially distributed cells as well as rare diffuse cells, and quantitatively deconvolute datasets from the Visium, Slide-seq, MERSCOPE, and CosMX technologies. Comparative analysis with a current alternative reference-free deconvolution tool also highlights CellsFromSpace's speed, scalability and accuracy in processing complex, even multisample datasets. CellsFromSpace also offers a user-friendly graphical interface enabling non-bioinformaticians to annotate and interpret components based on spatial distribution and contributor genes, and perform full downstream analysis.nnAVAILABILITY AND IMPLEMENTATION: CellsFromSpace (CFS) is distributed as an R package available from github at https://github.com/gustaveroussy/CFS along with tutorials, examples, and detailed documentation.},

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pubstate = {published},

tppubtype = {article}

}

@article{10.3389/fonc.2023.1166063,

title = {Longitudinal characterization of primary osteosarcoma and derived subcutaneous and orthotopic relapsed patient-derived xenograft models},

author = {Maria Eugenia Marques Costa and Robin Droit and Pierre Khneisser and Anne Gomez-Brouchet and Tiphaine Adam-de-Beaumais and Marie Nolla and Nicolas Signolles and Jacob Torrejon and Bérangère Lombard and Damarys Loew and Olivier Ayrault and Jean-Yves Scoazec and Birgit Geoerger and Gilles Vassal and Antonin Marchais and Nathalie Gaspar},

url = {https://www.frontiersin.org/articles/10.3389/fonc.2023.1166063},

doi = {10.3389/fonc.2023.1166063},

issn = {2234-943X},

year  = {2023},

date = {2023-01-01},

journal = {Frontiers in Oncology},

volume = {13},

abstract = {Osteosarcoma is a rare bone cancer in adolescents and young adults with a dismal prognosis because of metastatic disease and chemoresistance. Despite multiple clinical trials, no improvement in outcome has occurred in decades. There is an urgent need to better understand resistant and metastatic disease and to generate in vivo models from relapsed tumors. We developed eight new patient-derived xenograft (PDX) subcutaneous and orthotopic/paratibial models derived from patients with recurrent osteosarcoma and compared the genetic and transcriptomic landscapes of the disease progression at diagnosis and relapse with the matching PDX. Whole exome sequencing showed that driver and copy-number alterations are conserved from diagnosis to relapse, with the emergence of somatic alterations of genes mostly involved in DNA repair, cell cycle checkpoints, and chromosome organization. All PDX patients conserve most of the genetic alterations identified at relapse. At the transcriptomic level, tumor cells maintain their ossification, chondrocytic, and trans-differentiation programs during progression and implantation in PDX models, as identified at the radiological and histological levels. A more complex phenotype, like the interaction with immune cells and osteoclasts or cancer testis antigen expression, seemed conserved and was hardly identifiable by histology. Despite NSG mouse immunodeficiency, four of the PDX models partially reconstructed the vascular and immune-microenvironment observed in patients, among which the macrophagic TREM2/TYROBP axis expression, recently linked to immunosuppression. Our multimodal analysis of osteosarcoma progression and PDX models is a valuable resource to understand resistance and metastatic spread mechanisms, as well as for the exploration of novel therapeutic strategies for advanced osteosarcoma.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35292802,

title = {The European MAPPYACTS Trial: Precision Medicine Program in Pediatric and Adolescent Patients with Recurrent Malignancies},

author = {Pablo Berlanga and Gaelle Pierron and Ludovic Lacroix and Mathieu Chicard and Tiphaine Adam de Beaumais and Antonin Marchais and Anne C Harttrampf and Yasmine Iddir and Alicia Larive and Aroa Soriano Fernandez and Imene Hezam and Cecile Chevassus and Virginie Bernard and Sophie Cotteret and Jean-Yves Scoazec and Arnaud Gauthier and Samuel Abbou and Nadege Corradini and Nicolas André and Isabelle Aerts and Estelle Thebaud and Michela Casanova and Cormac Owens and Raquel Hladun-Alvaro and Stefan Michiels and Olivier Delattre and Gilles Vassal and Gudrun Schleiermacher and Birgit Geoerger},

doi = {10.1158/2159-8290.CD-21-1136},

issn = {2159-8290},

year  = {2022},

date = {2022-01-01},

journal = {Cancer Discov},

volume = {12},

number = {5},

pages = {1266--1281},

abstract = {ABSTRACT: MAPPYACTS (NCT02613962) is an international prospective precision medicine trial aiming to define tumor molecular profiles in pediatric patients with recurrent/refractory malignancies in order to suggest the most adapted salvage treatment. From February 2016 to July 2020, 787 patients were included in France, Italy, Ireland, and Spain. At least one genetic alteration leading to a targeted treatment suggestion was identified in 436 patients (69%) with successful sequencing; 10% of these alterations were considered "ready for routine use." Of 356 patients with follow-up beyond 12 months, 107 (30%) received one or more matched targeted therapies-56% of them within early clinical trials-mainly in the AcSé-ESMART platform trial (NCT02813135). Overall, matched treatment resulted in a 17% objective response rate, and of those patients with ready for routine use alterations, it was 38%. In patients with extracerebral tumors, 76% of actionable alterations detected in tumor tissue were also identified in circulating cell-free DNA (cfDNA).



SIGNIFICANCE: MAPPYACTS underlines the feasibility of molecular profiling at cancer recurrence in children on a multicenter, international level and demonstrates benefit for patients with selected key drivers. The use of cfDNA deserves validation in prospective studies. Our study highlights the need for innovative therapeutic proof-of-concept trials that address the underlying cancer complexity. This article is highlighted in the In This Issue feature, p. 1171.},

keywords = {},

pubstate = {published},

tppubtype = {article}

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@article{pmid35078815,

title = {Immune Infiltrate and Tumor Microenvironment Transcriptional Programs Stratify Pediatric Osteosarcoma into Prognostic Groups at Diagnosis},

author = {Antonin Marchais and Maria Eugenia Marques da Costa and Bastien Job and Rachid Abbas and Damien Drubay and Sophie Piperno-Neumann and Olivia Fromigué and Anne Gomez-Brouchet and Françoise Redini and Robin Droit and Cyril Lervat and Natacha Entze-Werle and Hélène Pacquement and Catherine Devoldere and Didier Cupissol and Damien Bodet and Virginie Gandemer and Marc Berger and Perrine Marec-Berard and Marta Jimenez and Gilles Vassal and Birgit Geoerger and Laurence Brugières and Nathalie Gaspar},

doi = {10.1158/0008-5472.CAN-20-4189},

issn = {1538-7445},

year  = {2022},

date = {2022-01-01},

journal = {Cancer Res},

volume = {82},

number = {6},

pages = {974--985},

abstract = {The outcomes of adolescents/young adults with osteosarcoma have not improved in decades. The chaotic karyotype of this rare tumor has precluded the identification of prognostic biomarkers and patient stratification. We reasoned that transcriptomic studies should overcome this genetic complexity. RNA sequencing (RNA-seq) of 79 osteosarcoma diagnostic biopsies identified stable independent components that recapitulate the tumor and microenvironment cell composition. Unsupervised classification of the independent components stratified this cohort into favorable (G1) and unfavorable (G2) prognostic tumors in terms of overall survival. Multivariate survival analysis ranked this stratification as the most influential variable. Functional characterization associated G1 tumors with innate immunity and G2 tumors with angiogenic, osteoclastic, and adipogenic activities as well as PPARγ pathway upregulation. A focused gene signature that predicted G1/G2 tumors from RNA-seq data was developed and validated within an independent cohort of 82 osteosarcomas. This signature was further validated with a custom NanoString panel in 96 additional osteosarcomas. This study thus proposes new biomarkers to detect high-risk patients and new therapeutic options for osteosarcoma.



SIGNIFICANCE: These findings indicate that the osteosarcoma microenvironment composition is a major feature to identify hard-to-treat patient tumors at diagnosis and define the biological pathways and potential actionable targets associated with these tumors.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33659950,

title = {Recent advances in understanding osteosarcoma and emerging therapies},

author = {Nathalie Gaspar and Maria Eugenia Marques da Costa and Olivia Fromigue and Robin Droit and Pablo Berlanga and Antonin Marchais},

doi = {10.12703/r/9-18},

issn = {2732-432X},

year  = {2020},

date = {2020-01-01},

journal = {Fac Rev},

volume = {9},

pages = {18},

abstract = {Osteosarcoma is the most common bone cancer in adolescents and young adults, but it is a rare cancer with no improvement in patient survival in the last four decades. The main problem of this bone tumor is its evolution toward lung metastatic disease, despite the current treatment strategy (chemotherapy and surgery). To further improve survival, there is a strong need for new therapies that control osteosarcoma cells with metastatic potential and their favoring tumor microenvironment (ME) from the diagnosis. However, the complexity and heterogeneity of those tumor cell genomic/epigenetic and biology, the diversity of tumor ME where it develops, the sparsity of appropriate preclinical models, and the heterogeneity of therapeutic trials have rendered the task difficult. No tumor- or ME-targeted drugs are routinely available in front-line treatment. This article presents up-to-date information from preclinical and clinical studies that were recently published or presented in recent meetings which we hope might help change the osteosarcoma treatment landscape and patient survival in the near future.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31319571,

title = {In-Vitro and In-Vivo Establishment and Characterization of Bioluminescent Orthotopic Chemotherapy-Resistant Human Osteosarcoma Models in NSG Mice},

author = {Maria Eugénia Marques da Costa and Antonin Marchais and Anne Gomez-Brouchet and Bastien Job and Noémie Assoun and Estelle Daudigeos-Dubus and Olivia Fromigué and Conceição Santos and Birgit Geoerger and Nathalie Gaspar},

doi = {10.3390/cancers11070997},

issn = {2072-6694},

year  = {2019},

date = {2019-07-01},

journal = {Cancers (Basel)},

volume = {11},

number = {7},

abstract = {Osteosarcoma, the most common bone malignancy with a peak incidence at adolescence, had no survival improvement since decades. Persistent problems are chemo-resistance and metastatic spread. We developed in-vitro osteosarcoma models resistant to chemotherapy and in-vivo bioluminescent orthotopic cell-derived-xenografts (CDX). Continuous increasing drug concentration cultures in-vitro resulted in five methotrexate (MTX)-resistant and one doxorubicin (DOXO)-resistant cell lines. Resistance persisted after drug removal except for MG-63. Different resistance mechanisms were identified, affecting drug transport and action mechanisms specific to methotrexate (RFC/SCL19A1 decrease, DHFR up-regulation) for MTX-resistant lines, or a multi-drug phenomenon (PgP up-regulation) for HOS-R/DOXO. Differential analysis of copy number abnormalities (aCGH) and gene expression (RNAseq) revealed changes of several chromosomic regions translated at transcriptomic level depending on drug and cell line, as well as different pathways implicated in invasive and metastatic potential (e.g., Fas, Metalloproteinases) and immunity (enrichment in HLA cluster genes in 6p21.3) in HOS-R/DOXO. Resistant-CDX models (HOS-R/MTX, HOS-R/DOXO and Saos-2-B-R/MTX) injected intratibially into NSG mice behaved as their parental counterpart at primary tumor site; however, they exhibited a slower growth rate and lower metastatic spread, although they retained resistance and CGH main characteristics without drug pressure. These models represent valuable tools to explore resistance mechanisms and new therapies in osteosarcoma.},

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pubstate = {published},

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}