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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.

Supplementary Figure from Immune Infiltrate and Tumor Microenvironment Transcriptional Programs Stratify Pediatric Osteosarcoma into Prognostic Groups at Diagnosis

Supplementary Table from Immune Infiltrate and Tumor Microenvironment Transcriptional Programs Stratify Pediatric Osteosarcoma into Prognostic Groups at Diagnosis

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.

Pediatric patients with recurrent and refractory cancers are in most need for new treatments. This study developed patient-derived-xenograft (PDX) models within the European MAPPYACTS cancer precision medicine trial (NCT02613962). To date, 131 PDX models were established following heterotopical and/or orthotopical implantation in immunocompromised mice: 76 sarcomas, 25 other solid tumors, 12 central nervous system tumors, 15 acute leukemias, and 3 lymphomas. PDX establishment rate was 43%. Histology, whole exome and RNA sequencing revealed a high concordance with the primary patient’s tumor profile, human leukocyte-antigen characteristics and specific metabolic pathway signatures. A detailed patient molecular characterization, including specific mutations prioritized in the clinical molecular tumor boards are provided. Ninety models were shared with the IMI2 ITCC Paediatric Preclinical Proof-of-concept Platform (IMI2 ITCC-P4) for further exploitation. This new PDX biobank of unique recurrent childhood cancers provides an essential support for basic and translational research and new treatments development in advanced pediatric malignancies.