Longitudinal characterization of primary osteosarcoma and derived subcutaneous and orthotopic relapsed patient-derived xenograft models

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: RNAseq; bone; omics; osteosarcoma; patient-derived xenograft.

Figure 1

Tumor engraftment, radiological, and morphological characteristics of the eight osteosarcoma PDX models implanted subcutaneously and paratibially in NSG mice. (A) Origin of osteosarcoma patient samples used for PDX development. (B) Patient biopsy/surgery origin site used for PDX development. (C) PDX development from patient sample implanted at P0 until implantation at P2. The underlined implantation method represents the method used in each passage to perform the next passage. At each passage, the method underlined was used to perform the next passage. (D) Experimental design of PDX development; (E, F) Tumor growth of subcutaneous models in passage 0 and passage 2, respectively. *PDX was developed from a patient-frozen sample. (G) Radiological and morphological characteristics of the PDX GR-OS-15 primary tumor and metastases: CT scan images from the subcutaneous tumor (a) and the leg bearing the paratibial tumor (f and g) and normal leg (h), obtained with an Ivis Spectrum scan. Histology was performed for the primary tumor of the subcutaneous model (b), the paratibial tumor (i) and the normal leg (j), and the metastases of the subcutaneous (c–e) and paratibial (k–o) models. The short white arrows show osteocondensation, the long white arrows osteolysis, the long black arrows osteoid matrix (orange color), and the short black arrows mark metastases. TL, tumor leg; NL, normal leg. (H) Boxplot of the percentage of reads aligned on tumor cells (human fraction) or the microenvironment (mouse fraction) in PDX inferred either from the Xenome RNA-Seq or WES analyses.

Figure 2

Genomic landscape of osteosarcoma subcutaneous and paratibial (orthotopic) PDX models compared to their derived relapsed metastatic tumor and the corresponding primary tumor at diagnosis. (A) Circos plot regrouping all the genetic alterations (somatic mutations, CNA, fusion transcripts, and expression levels). (B) Oncoprint of all the genetic alterations (somatic mutations, CNAs, and fusions) for the genes of the Cancer Gene Census (CGC). (C) Jaccard distance between times of samples for the somatic mutations. (D) Jaccard distance between times of samples for the CNA. (E) Conservation of the fusions through time and patients. Dia, diagnosis; Rel, relapse; pt, paratibial; sc, subcutaneous.

Figure 3

Tumor transcriptomic comparison between osteosarcoma PDX models and corresponding human samples at relapse and diagnosis. (A) UMAP of the selected tumor principal components (TPCs) for the tumor fraction; (B) Geneset enrichment analysis of each component based on gene contribution to the TPC; The sign of the enrichment score represents the opposite functional enrichment described by the same principal component (C) A word cloud illustrating the gene contributing the most to each component, negatively (blue) or positively (red); (D) The contribution of each sample to each TPC classified by patient. The sign of the contribution illustrates if the sample participates in the negative functional enrichment fraction of the corresponding principal component shown in (C). Diag, diagnosis; pt, paratibial; sc, subcutaneous.

Figure 4

Tumor microenvironment composition comparison between osteosarcoma PDX models and corresponding human samples at relapse and diagnosis. (A) Identification of F4/80⁺ cells in eight paratibial PDX models of osteosarcoma; (B) Identification of CD31 cells in eight paratibial PDX models of osteosarcoma; (C) UMAP of the four first microenvironment principal components (MPCs); (D) Geneset enrichment analysis of each component according to genes positively or negatively contributing to MPC; The sign of the enrichment score represents the opposite functional enrichment described by the same principal component (E) A word cloud illustrating the gene contributing the most to each component, negatively (blue) or positively (red); (F) Contribution of each sample to each MPC classified by patient. The sign of the contribution illustrates if the sample contributes to the negative functional enrichment fraction of the corresponding principal component shown in (D) Diag, diagnosis; pt, paratibial; sc, subcutaneous. (G) Boxplot showing the log-transformed of the gene expression of TREM2 and TYROBP at diagnosis, relapse, and in the mouse fraction of the paratibal and subcutaneous PDX models.

Figure 5

Tumor alterations and metastatic development for each patient at diagnosis and at relapse and for their derived subcutaneous and paratibial PDX models. All depicted alterations were conserved from either diagnosis (blue) or relapse (red) to PDX models (green and gray for paratibial and subcutaneous, respectively).