Cancer risk and tumour spectrum in 172 patients with a germline SUFU pathogenic variation : a collaborative study of the SIOPE Host Genome Working Group

Background Little is known about risks associated with germline SUFU pathogenic variants (PVs) known as a cancer predisposition syndrome. Methods To study tumour risks, we have analysed data of a large cohort of 45 unpublished patients with a germline SUFU PV completed with 127 previously published patients. To reduce the ascertainment bias due to index patient selection, the risk of tumours was evaluated in relatives with SUFU PV (89 patients) using the Nelson-Aalen estimator. Results Overall, 117/172 (68%) SUFU PV carriers developed at least one tumour: medulloblastoma (MB) (86 patients), basal cell carcinoma (BCC) (25 patients), meningioma (20 patients) and gonadal tumours (11 patients). Thirty-three of them (28%) had multiple tumours. Median age at diagnosis of MB, gonadal tumour, first BCC and first meningioma were 1.5, 14, 40 and 44 years, respectively. Follow-up data were available for 160 patients (137 remained alive and 23 died). The cumulative incidence of tumours in relatives was 14.4% (95% CI 6.8 to 21.4), 18.2% (95% CI 9.7 to 25.9) and 44.1% (95% CI 29.7 to 55.5) at the age of 5, 20 and 50 years, respectively. The cumulative risk of an MB, gonadal tumour, BCC and meningioma at age 50 years was: 13.3% (95% CI 6 to 20.1), 4.6% (95% CI 0 to 9.7), 28.5% (95% CI 13.4 to 40.9) and 5.2% (95% CI 0 to 12), respectively. Sixty-four different PVs were reported across the entire SUFU gene and inherited in 73% of cases in which inheritance could be evaluated. Conclusion Germline SUFU PV carriers have a life-long increased risk of tumours with a spectrum dominated by MB before the age of 5, gonadal tumours during adolescence and BCC and meningioma in adulthood, justifying fine-tuned surveillance programmes.Peer reviewe

ERS: A simple scoring system to predict early recurrence after surgical resection for hepatocellular carcinoma.

peer reviewed[en] BACKGROUND: Surgical resection (SR) is a potentially curative treatment of hepatocellular carcinoma (HCC) hampered by high rates of recurrence. New drugs are tested in the adjuvant setting, but standardised risk stratification tools of HCC recurrence are lacking. OBJECTIVES: To develop and validate a simple scoring system to predict 2-year recurrence after SR for HCC. METHODS: 2359 treatment-naïve patients who underwent SR for HCC in 17 centres in Europe and Asia between 2004 and 2017 were divided into a development (DS; n = 1558) and validation set (VS; n = 801) by random sampling of participating centres. The Early Recurrence Score (ERS) was generated using variables associated with 2-year recurrence in the DS and validated in the VS. RESULTS: Variables associated with 2-year recurrence in the DS were (with associated points) alpha-fetoprotein (100: 3), size of largest nodule (≥40 mm: 1), multifocality (yes: 2), satellite nodules (yes: 2), vascular invasion (yes: 1) and surgical margin (positive R1: 2). The sum of points provided a score ranging from 0 to 11, allowing stratification into four levels of 2-year recurrence risk (Wolbers' C-indices 66.8% DS and 68.4% VS), with excellent calibration according to risk categories. Wolber's and Harrell's C-indices apparent values were systematically higher for ERS when compared to Early Recurrence After Surgery for Liver tumour post-operative model to predict time to early recurrence or recurrence-free survival. CONCLUSIONS: ERS is a user-friendly staging system identifying four levels of early recurrence risk after SR and a robust tool to design personalised surveillance strategies and adjuvant therapy trials

The Athena X-ray Integral Field Unit: a consolidated design for the system requirement review of the preliminary definition phase

The Athena X-ray Integral Unit (X-IFU) is the high resolution X-ray spectrometer, studied since 2015 for flying in the mid-30s on the Athena space X-ray Observatory, a versatile observatory designed to address the Hot and Energetic Universe science theme, selected in November 2013 by the Survey Science Committee. Based on a large format array of Transition Edge Sensors (TES), it aims to provide spatially resolved X-ray spectroscopy, with a spectral resolution of 2.5 eV (up to 7 keV) over an hexagonal field of view of 5 arc minutes (equivalent diameter). The X-IFU entered its System Requirement Review (SRR) in June 2022, at about the same time when ESA called for an overall X-IFU redesign (including the X-IFU cryostat and the cooling chain), due to an unanticipated cost overrun of Athena. In this paper, after illustrating the breakthrough capabilities of the X-IFU, we describe the instrument as presented at its SRR, browsing through all the subsystems and associated requirements. We then show the instrument budgets, with a particular emphasis on the anticipated budgets of some of its key performance parameters. Finally we briefly discuss on the ongoing key technology demonstration activities, the calibration and the activities foreseen in the X-IFU Instrument Science Center, and touch on communication and outreach activities, the consortium organisation, and finally on the life cycle assessment of X-IFU aiming at minimising the environmental footprint, associated with the development of the instrument. Thanks to the studies conducted so far on X-IFU, it is expected that along the design-to-cost exercise requested by ESA, the X-IFU will maintain flagship capabilities in spatially resolved high resolution X-ray spectroscopy, enabling most of the original X-IFU related scientific objectives of the Athena mission to be retained. (abridged).Comment: 48 pages, 29 figures, Accepted for publication in Experimental Astronomy with minor editin

The Athena X-ray Integral Field Unit: a consolidated design for the system requirement review of the preliminary definition phase

The Athena X-ray Integral Unit (X-IFU) is the high resolution X-ray spectrometer studied since 2015 for flying in the mid-30s on the Athena space X-ray Observatory. Athena is a versatile observatory designed to address the Hot and Energetic Universe science theme, as selected in November 2013 by the Survey Science Committee. Based on a large format array of Transition Edge Sensors (TES), X-IFU aims to provide spatially resolved X-ray spectroscopy, with a spectral resolution of 2.5 eV (up to 7 keV) over a hexagonal field of view of 5 arc minutes (equivalent diameter). The X-IFU entered its System Requirement Review (SRR) in June 2022, at about the same time when ESA called for an overall X-IFU redesign (including the X-IFU cryostat and the cooling chain), due to an unanticipated cost overrun of Athena. In this paper, after illustrating the breakthrough capabilities of the X-IFU, we describe the instrument as presented at its SRR (i.e. in the course of its preliminary definition phase, so-called B1), browsing through all the subsystems and associated requirements. We then show the instrument budgets, with a particular emphasis on the anticipated budgets of some of its key performance parameters, such as the instrument efficiency, spectral resolution, energy scale knowledge, count rate capability, non X-ray background and target of opportunity efficiency. Finally, we briefly discuss the ongoing key technology demonstration activities, the calibration and the activities foreseen in the X-IFU Instrument Science Center, touch on communication and outreach activities, the consortium organisation and the life cycle assessment of X-IFU aiming at minimising the environmental footprint, associated with the development of the instrument. Thanks to the studies conducted so far on X-IFU, it is expected that along the design-to-cost exercise requested by ESA, the X-IFU will maintain flagship capabilities in spatially resolved high resolution X-ray spectroscopy, enabling most of the original X-IFU related scientific objectives of the Athena mission to be retained. The X-IFU will be provided by an international consortium led by France, The Netherlands and Italy, with ESA member state contributions from Belgium, Czech Republic, Finland, Germany, Poland, Spain, Switzerland, with additional contributions from the United States and Japan.The French contribution to X-IFU is funded by CNES, CNRS and CEA. This work has been also supported by ASI (Italian Space Agency) through the Contract 2019-27-HH.0, and by the ESA (European Space Agency) Core Technology Program (CTP) Contract No. 4000114932/15/NL/BW and the AREMBES - ESA CTP No.4000116655/16/NL/BW. This publication is part of grant RTI2018-096686-B-C21 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”. This publication is part of grant RTI2018-096686-B-C21 and PID2020-115325GB-C31 funded by MCIN/AEI/10.13039/501100011033

Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease

Background: Experimental and clinical data suggest that reducing inflammation without affecting lipid levels may reduce the risk of cardiovascular disease. Yet, the inflammatory hypothesis of atherothrombosis has remained unproved. Methods: We conducted a randomized, double-blind trial of canakinumab, a therapeutic monoclonal antibody targeting interleukin-1β, involving 10,061 patients with previous myocardial infarction and a high-sensitivity C-reactive protein level of 2 mg or more per liter. The trial compared three doses of canakinumab (50 mg, 150 mg, and 300 mg, administered subcutaneously every 3 months) with placebo. The primary efficacy end point was nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. RESULTS: At 48 months, the median reduction from baseline in the high-sensitivity C-reactive protein level was 26 percentage points greater in the group that received the 50-mg dose of canakinumab, 37 percentage points greater in the 150-mg group, and 41 percentage points greater in the 300-mg group than in the placebo group. Canakinumab did not reduce lipid levels from baseline. At a median follow-up of 3.7 years, the incidence rate for the primary end point was 4.50 events per 100 person-years in the placebo group, 4.11 events per 100 person-years in the 50-mg group, 3.86 events per 100 person-years in the 150-mg group, and 3.90 events per 100 person-years in the 300-mg group. The hazard ratios as compared with placebo were as follows: in the 50-mg group, 0.93 (95% confidence interval [CI], 0.80 to 1.07; P = 0.30); in the 150-mg group, 0.85 (95% CI, 0.74 to 0.98; P = 0.021); and in the 300-mg group, 0.86 (95% CI, 0.75 to 0.99; P = 0.031). The 150-mg dose, but not the other doses, met the prespecified multiplicity-adjusted threshold for statistical significance for the primary end point and the secondary end point that additionally included hospitalization for unstable angina that led to urgent revascularization (hazard ratio vs. placebo, 0.83; 95% CI, 0.73 to 0.95; P = 0.005). Canakinumab was associated with a higher incidence of fatal infection than was placebo. There was no significant difference in all-cause mortality (hazard ratio for all canakinumab doses vs. placebo, 0.94; 95% CI, 0.83 to 1.06; P = 0.31). Conclusions: Antiinflammatory therapy targeting the interleukin-1β innate immunity pathway with canakinumab at a dose of 150 mg every 3 months led to a significantly lower rate of recurrent cardiovascular events than placebo, independent of lipid-level lowering. (Funded by Novartis; CANTOS ClinicalTrials.gov number, NCT01327846.

The Athena X-ray Integral Field Unit: a consolidated design for the system requirement review of the preliminary definition phase

Instrumentatio

Oncogenèse et infiltrat immunitaire dans les sarcomes

Les sarcomes sont des cancers d’origine mésenchymateuse qui comprennent plus d’une centaine d’entités. Ce sont pour la plupart des maladies rares qui peuvent survenir à tout âge, y compris pendant l’enfance et la jeune adolescence. En raison de leur rareté et diversité, le diagnostic en est souvent erroné ou retardé. Le pronostic est généralement sombre dans les formes avancées et métastatiques, et la plupart des traitements reposent actuellement sur des chimiothérapies non spécifiques et très toxiques. Il y a donc un besoin urgent d’améliorer le diagnostic des sarcomes et développer de nouvelles approches thérapeutiques pour ces cancers.Le séquençage de l’ARN (RNA-seq) est une technique prometteuse pour le diagnostic des sarcomes, notamment dans le cas des sarcomes liés à des translocations qui sont caractérisés par des translocations chromosomiques à l’origine de gènes de fusion, par exemple EWSR1-FLI1 dans le sarcome d’Ewing. A l’aide de la base de données du RNA-seq de sarcomes de patients de l’Institut Curie, j’ai exploré le paysage transcriptomique des ces cancers et utilisé des techniques d’apprentissage machine (machine learning) et d’apprentissage profond (deep learning) pour prédire le type de sarcome à l’aide du RNA-seq. Ce travail a ensuite permis le développement d’un outil actuellement utilisé à l’Institut Curie pour prédire la tumeur d’origine de cancers de primitif inconnu et ainsi améliorer le diagnostic et le pronostic de patients en pratique clinique courante.Au cours de la dernière décennie, l’immunothérapie a été à l’origine d’une révolution dans le traitement de multiples cancers. Cependant, elle n’a eu qu’un succès très limité dans les sarcomes qui sont généralement considérés comme des tumeurs non « immunogéniques ». En effet, la plupart des sarcomes, notamment liés aux translocations, ont une charge mutationnelle très faible. Or ce dernier facteur est considéré comme l’un des principaux générateurs de néoantigènes tumoraux qui servent de cible au système immunitaire. Pour étudier plus en détail la possibilité d’une réponse immunitaire dans les sarcomes, j’ai caractérisé le microenvironnement tumoral immunitaire et les répertoires lymphocytaires dans de nombreux types de sarcomes à l’aide du RNA-seq d’échantillons tumoraux. Bien que la plupart sont effectivement peu infiltrés par des cellules du système immunitaire, il existe des exceptions qui font penser que l’immunothérapie pourrait être efficace dans certains cas. Une autre piste prometteuse pour l’immunothérapie des sarcomes a été l’identification de nouveaux transcrits spécifiques dans de nombreux types de sarcomes liés à des translocations. Ces « néotranscrits » sont induits par le facteur de transcription oncogénique chimérique caractéristique de la tumeur, par exemple EWSR1-FLI1 dans le sarcome d’Ewing. Certains d’entre eux sont traduits par les ribosomes en peptides. Ils représentent donc une source potentielle de néoantigènes publics spécifiques de la tumeur pour lesapproches d’immunothérapie dans les sarcomes liés à des translocations.Pour caractériser en détail le microenvironnement immunitaire et les processus oncogéniques de sarcomes spécifiques, certains d’entre eux ont été étudiés par du RNA-seq à l’échelle unicellulaire (single-cell RNA-seq), notamment les liposarcomes dédifférenciés (DDLPS). Cette technique a mis en évidence une infiltration plus importante de cellules immunitaires dans le compartiment dédifférencié de la tumeur, ainsi qu’un phénotype « épuisé » (exhausted) et immunosuppresseur de ces cellules. Elle a aussi permis de caractériser les processus oncogéniques des DDLPS, notamment la relation entre les cellules bien différenciées et « dédifférenciées » au sein d’une même tumeur.Sarcomas are cancers of mesenchymal origin that comprise more than a hundred different entities. They are mostly rare diseases that occur at all ages, including in children and young adolescents. Due to their rarity and diversity, diagnosis is often missed or delayed. Prognosis is generally poor in cases of advanced or metastatic disease and most treatment approaches rely on unspecific and highly toxic chemotherapy. There is thus an unmet need to improve the diagnosis of sarcomas and develop novel therapeutic approaches for these diseases. RNA sequencing (RNA-seq) is a promising approach for the diagnosis of sarcomas, especially for translocation-related sarcomas that are characterized by chromosome translocations giving rise to fusion genes, such as EWSR1-FLI1 in Ewing sarcoma. Using RNA-seq data of sarcomas of patients profiled at the Institut Curie, I explored the transcriptomic landscape of sarcomas and used machine learning and deep learning techniques to predict sarcoma type based on RNA-seq. This work led to the development of a tool currently in use at the Institut Curie to predict the origin of cancers of unknown primary and improve the diagnosis and prognosis of individual patients in clinical practice.Immunotherapy has revolutionized cancer care for the last decade, however it has had only limited success in sarcomas, supposedly because they are not “immunogenic”. Indeed, most sarcomas, especially translocation-related ones, have a very low tumor mutational burden, which is believed to be the main driving force in the generation of tumor neoantigens recognized by the immune system. To gain further insight into the potential of immune response in sarcoma, I characterized the immune microenvironment and lymphocyte repertoires of multiple types of sarcomas using RNA-seq of tumor samples. While most of them were indeed poorly infiltrated by cells of the immune system, there were some exceptions to this rule suggesting that immunotherapy should be considered in some cases.Another promising finding for immunotherapy of sarcomas was the identification of novel tumor-specific transcripts in multiple types of translocation-related sarcomas. These “neotranscripts” were driven by their characteristic oncogenic chimeric transcription factors such as EWSR1-FLI1 in Ewing sarcoma; some of them were found to be translated by ribosomes into peptides. Therefore, these may represent a source of tumor-specific public neoantigens for immunotherapies of these translocation-related sarcomas.To characterize in detail the immune microenvironment and oncogenic processes of specific sarcomas, single-cell RNA-seq was performed for some of them, notably dedifferentiated liposarcomas (DDLPS). It revealed higher infiltration by immune cells in the dedifferentiated compartment of the tumor, but with more exhausted and immunosuppressive phenotypes. It also allowed to characterize the oncogenic processes of DDLPS and notably the relationship between dedifferentiated and well-differentiated cells inside the same tumor

Oncogenèse et infiltrat immunitaire dans les sarcomes

Sarcomas are cancers of mesenchymal origin that comprise more than a hundred different entities. They are mostly rare diseases that occur at all ages, including in children and young adolescents. Due to their rarity and diversity, diagnosis is often missed or delayed. Prognosis is generally poor in cases of advanced or metastatic disease and most treatment approaches rely on unspecific and highly toxic chemotherapy. There is thus an unmet need to improve the diagnosis of sarcomas and develop novel therapeutic approaches for these diseases. RNA sequencing (RNA-seq) is a promising approach for the diagnosis of sarcomas, especially for translocation-related sarcomas that are characterized by chromosome translocations giving rise to fusion genes, such as EWSR1-FLI1 in Ewing sarcoma. Using RNA-seq data of sarcomas of patients profiled at the Institut Curie, I explored the transcriptomic landscape of sarcomas and used machine learning and deep learning techniques to predict sarcoma type based on RNA-seq. This work led to the development of a tool currently in use at the Institut Curie to predict the origin of cancers of unknown primary and improve the diagnosis and prognosis of individual patients in clinical practice.Immunotherapy has revolutionized cancer care for the last decade, however it has had only limited success in sarcomas, supposedly because they are not “immunogenic”. Indeed, most sarcomas, especially translocation-related ones, have a very low tumor mutational burden, which is believed to be the main driving force in the generation of tumor neoantigens recognized by the immune system. To gain further insight into the potential of immune response in sarcoma, I characterized the immune microenvironment and lymphocyte repertoires of multiple types of sarcomas using RNA-seq of tumor samples. While most of them were indeed poorly infiltrated by cells of the immune system, there were some exceptions to this rule suggesting that immunotherapy should be considered in some cases.Another promising finding for immunotherapy of sarcomas was the identification of novel tumor-specific transcripts in multiple types of translocation-related sarcomas. These “neotranscripts” were driven by their characteristic oncogenic chimeric transcription factors such as EWSR1-FLI1 in Ewing sarcoma; some of them were found to be translated by ribosomes into peptides. Therefore, these may represent a source of tumor-specific public neoantigens for immunotherapies of these translocation-related sarcomas.To characterize in detail the immune microenvironment and oncogenic processes of specific sarcomas, single-cell RNA-seq was performed for some of them, notably dedifferentiated liposarcomas (DDLPS). It revealed higher infiltration by immune cells in the dedifferentiated compartment of the tumor, but with more exhausted and immunosuppressive phenotypes. It also allowed to characterize the oncogenic processes of DDLPS and notably the relationship between dedifferentiated and well-differentiated cells inside the same tumor.Les sarcomes sont des cancers d’origine mésenchymateuse qui comprennent plus d’une centaine d’entités. Ce sont pour la plupart des maladies rares qui peuvent survenir à tout âge, y compris pendant l’enfance et la jeune adolescence. En raison de leur rareté et diversité, le diagnostic en est souvent erroné ou retardé. Le pronostic est généralement sombre dans les formes avancées et métastatiques, et la plupart des traitements reposent actuellement sur des chimiothérapies non spécifiques et très toxiques. Il y a donc un besoin urgent d’améliorer le diagnostic des sarcomes et développer de nouvelles approches thérapeutiques pour ces cancers.Le séquençage de l’ARN (RNA-seq) est une technique prometteuse pour le diagnostic des sarcomes, notamment dans le cas des sarcomes liés à des translocations qui sont caractérisés par des translocations chromosomiques à l’origine de gènes de fusion, par exemple EWSR1-FLI1 dans le sarcome d’Ewing. A l’aide de la base de données du RNA-seq de sarcomes de patients de l’Institut Curie, j’ai exploré le paysage transcriptomique des ces cancers et utilisé des techniques d’apprentissage machine (machine learning) et d’apprentissage profond (deep learning) pour prédire le type de sarcome à l’aide du RNA-seq. Ce travail a ensuite permis le développement d’un outil actuellement utilisé à l’Institut Curie pour prédire la tumeur d’origine de cancers de primitif inconnu et ainsi améliorer le diagnostic et le pronostic de patients en pratique clinique courante.Au cours de la dernière décennie, l’immunothérapie a été à l’origine d’une révolution dans le traitement de multiples cancers. Cependant, elle n’a eu qu’un succès très limité dans les sarcomes qui sont généralement considérés comme des tumeurs non « immunogéniques ». En effet, la plupart des sarcomes, notamment liés aux translocations, ont une charge mutationnelle très faible. Or ce dernier facteur est considéré comme l’un des principaux générateurs de néoantigènes tumoraux qui servent de cible au système immunitaire. Pour étudier plus en détail la possibilité d’une réponse immunitaire dans les sarcomes, j’ai caractérisé le microenvironnement tumoral immunitaire et les répertoires lymphocytaires dans de nombreux types de sarcomes à l’aide du RNA-seq d’échantillons tumoraux. Bien que la plupart sont effectivement peu infiltrés par des cellules du système immunitaire, il existe des exceptions qui font penser que l’immunothérapie pourrait être efficace dans certains cas. Une autre piste prometteuse pour l’immunothérapie des sarcomes a été l’identification de nouveaux transcrits spécifiques dans de nombreux types de sarcomes liés à des translocations. Ces « néotranscrits » sont induits par le facteur de transcription oncogénique chimérique caractéristique de la tumeur, par exemple EWSR1-FLI1 dans le sarcome d’Ewing. Certains d’entre eux sont traduits par les ribosomes en peptides. Ils représentent donc une source potentielle de néoantigènes publics spécifiques de la tumeur pour lesapproches d’immunothérapie dans les sarcomes liés à des translocations.Pour caractériser en détail le microenvironnement immunitaire et les processus oncogéniques de sarcomes spécifiques, certains d’entre eux ont été étudiés par du RNA-seq à l’échelle unicellulaire (single-cell RNA-seq), notamment les liposarcomes dédifférenciés (DDLPS). Cette technique a mis en évidence une infiltration plus importante de cellules immunitaires dans le compartiment dédifférencié de la tumeur, ainsi qu’un phénotype « épuisé » (exhausted) et immunosuppresseur de ces cellules. Elle a aussi permis de caractériser les processus oncogéniques des DDLPS, notamment la relation entre les cellules bien différenciées et « dédifférenciées » au sein d’une même tumeur

Oncogenèse et infiltrat immunitaire dans les sarcomes

Sarcomas are cancers of mesenchymal origin that comprise more than a hundred different entities. They are mostly rare diseases that occur at all ages, including in children and young adolescents. Due to their rarity and diversity, diagnosis is often missed or delayed. Prognosis is generally poor in cases of advanced or metastatic disease and most treatment approaches rely on unspecific and highly toxic chemotherapy. There is thus an unmet need to improve the diagnosis of sarcomas and develop novel therapeutic approaches for these diseases. RNA sequencing (RNA-seq) is a promising approach for the diagnosis of sarcomas, especially for translocation-related sarcomas that are characterized by chromosome translocations giving rise to fusion genes, such as EWSR1-FLI1 in Ewing sarcoma. Using RNA-seq data of sarcomas of patients profiled at the Institut Curie, I explored the transcriptomic landscape of sarcomas and used machine learning and deep learning techniques to predict sarcoma type based on RNA-seq. This work led to the development of a tool currently in use at the Institut Curie to predict the origin of cancers of unknown primary and improve the diagnosis and prognosis of individual patients in clinical practice.Immunotherapy has revolutionized cancer care for the last decade, however it has had only limited success in sarcomas, supposedly because they are not “immunogenic”. Indeed, most sarcomas, especially translocation-related ones, have a very low tumor mutational burden, which is believed to be the main driving force in the generation of tumor neoantigens recognized by the immune system. To gain further insight into the potential of immune response in sarcoma, I characterized the immune microenvironment and lymphocyte repertoires of multiple types of sarcomas using RNA-seq of tumor samples. While most of them were indeed poorly infiltrated by cells of the immune system, there were some exceptions to this rule suggesting that immunotherapy should be considered in some cases.Another promising finding for immunotherapy of sarcomas was the identification of novel tumor-specific transcripts in multiple types of translocation-related sarcomas. These “neotranscripts” were driven by their characteristic oncogenic chimeric transcription factors such as EWSR1-FLI1 in Ewing sarcoma; some of them were found to be translated by ribosomes into peptides. Therefore, these may represent a source of tumor-specific public neoantigens for immunotherapies of these translocation-related sarcomas.To characterize in detail the immune microenvironment and oncogenic processes of specific sarcomas, single-cell RNA-seq was performed for some of them, notably dedifferentiated liposarcomas (DDLPS). It revealed higher infiltration by immune cells in the dedifferentiated compartment of the tumor, but with more exhausted and immunosuppressive phenotypes. It also allowed to characterize the oncogenic processes of DDLPS and notably the relationship between dedifferentiated and well-differentiated cells inside the same tumor.Les sarcomes sont des cancers d’origine mésenchymateuse qui comprennent plus d’une centaine d’entités. Ce sont pour la plupart des maladies rares qui peuvent survenir à tout âge, y compris pendant l’enfance et la jeune adolescence. En raison de leur rareté et diversité, le diagnostic en est souvent erroné ou retardé. Le pronostic est généralement sombre dans les formes avancées et métastatiques, et la plupart des traitements reposent actuellement sur des chimiothérapies non spécifiques et très toxiques. Il y a donc un besoin urgent d’améliorer le diagnostic des sarcomes et développer de nouvelles approches thérapeutiques pour ces cancers.Le séquençage de l’ARN (RNA-seq) est une technique prometteuse pour le diagnostic des sarcomes, notamment dans le cas des sarcomes liés à des translocations qui sont caractérisés par des translocations chromosomiques à l’origine de gènes de fusion, par exemple EWSR1-FLI1 dans le sarcome d’Ewing. A l’aide de la base de données du RNA-seq de sarcomes de patients de l’Institut Curie, j’ai exploré le paysage transcriptomique des ces cancers et utilisé des techniques d’apprentissage machine (machine learning) et d’apprentissage profond (deep learning) pour prédire le type de sarcome à l’aide du RNA-seq. Ce travail a ensuite permis le développement d’un outil actuellement utilisé à l’Institut Curie pour prédire la tumeur d’origine de cancers de primitif inconnu et ainsi améliorer le diagnostic et le pronostic de patients en pratique clinique courante.Au cours de la dernière décennie, l’immunothérapie a été à l’origine d’une révolution dans le traitement de multiples cancers. Cependant, elle n’a eu qu’un succès très limité dans les sarcomes qui sont généralement considérés comme des tumeurs non « immunogéniques ». En effet, la plupart des sarcomes, notamment liés aux translocations, ont une charge mutationnelle très faible. Or ce dernier facteur est considéré comme l’un des principaux générateurs de néoantigènes tumoraux qui servent de cible au système immunitaire. Pour étudier plus en détail la possibilité d’une réponse immunitaire dans les sarcomes, j’ai caractérisé le microenvironnement tumoral immunitaire et les répertoires lymphocytaires dans de nombreux types de sarcomes à l’aide du RNA-seq d’échantillons tumoraux. Bien que la plupart sont effectivement peu infiltrés par des cellules du système immunitaire, il existe des exceptions qui font penser que l’immunothérapie pourrait être efficace dans certains cas. Une autre piste prometteuse pour l’immunothérapie des sarcomes a été l’identification de nouveaux transcrits spécifiques dans de nombreux types de sarcomes liés à des translocations. Ces « néotranscrits » sont induits par le facteur de transcription oncogénique chimérique caractéristique de la tumeur, par exemple EWSR1-FLI1 dans le sarcome d’Ewing. Certains d’entre eux sont traduits par les ribosomes en peptides. Ils représentent donc une source potentielle de néoantigènes publics spécifiques de la tumeur pour lesapproches d’immunothérapie dans les sarcomes liés à des translocations.Pour caractériser en détail le microenvironnement immunitaire et les processus oncogéniques de sarcomes spécifiques, certains d’entre eux ont été étudiés par du RNA-seq à l’échelle unicellulaire (single-cell RNA-seq), notamment les liposarcomes dédifférenciés (DDLPS). Cette technique a mis en évidence une infiltration plus importante de cellules immunitaires dans le compartiment dédifférencié de la tumeur, ainsi qu’un phénotype « épuisé » (exhausted) et immunosuppresseur de ces cellules. Elle a aussi permis de caractériser les processus oncogéniques des DDLPS, notamment la relation entre les cellules bien différenciées et « dédifférenciées » au sein d’une même tumeur

The Molecular Biology of Soft Tissue Sarcomas: Current Knowledge and Future Perspectives

Soft tissue sarcomas are malignant tumors of mesenchymal origin, encompassing a large spectrum of entities that were historically classified according to their histological characteristics. Over the last decades, molecular biology has allowed a better characterization of these tumors, leading to the incorporation of multiple molecular features in the latest classification of sarcomas as well as to molecularly-guided therapeutic strategies. This review discusses the main uses of molecular biology in current practice for the diagnosis and treatment of soft tissue sarcomas, in addition to perspectives for this rapidly evolving field of research