Sulforaphane (SFN) is a naturally-occurring isothiocyanate best known for its role as an indirect antioxidant. Notwithstanding, in different cancer cell lines, SFN may promote the accumulation of reactive oxygen species (ROS) and cause cell death e.g. by apoptosis. Osteosarcoma often becomes chemoresistant, and new molecular targets to prevent drug resistance are needed. Here, we aimed to determine the effect of SFN on ROS levels and to identify key biomarkers leading to ROS unbalance and apoptosis in the p53-null MG-63 osteosarcoma cell line. MG-63 cells were exposed to SFN for up to 48 h. At 10 μM concentration or higher, SFN decreased cell viability, increased the%early apoptotic cells and increased caspase 3 activity. At these higher doses, SFN increased ROS levels, which correlated with apoptotic endpoints and cell viability decline. In exposed cells, gene expression analysis revealed only partial induction of phase-2 detoxification genes. More importantly, SFN inhibited ROS-scavenging enzymes and impaired glutathione recycling, as evidenced by inhibition of glutathione reductase (GR) activity and combined inhibition of glutathione peroxidase (GPx) gene expression and enzyme activity. In conclusion, SFN induced oxidative stress and apoptosis via a p53-independent mechanism. GPx expression and activity were found associated with ROS accumulation in MG-63 cells and are potential biomarkers for the efficacy of ROS-inducing agents e.g. as co-adjuvant drugs in osteosarcoma.

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.

Purpose: ALK-activating mutations are identified in approximately 10% of newly diagnosed neuroblastomas and ALK amplifications in a further 1%–2% of cases. Lorlatinib, a third-generation anaplastic lymphoma kinase (ALK) inhibitor, will soon be given alongside induction chemotherapy for children with ALK-aberrant neuroblastoma. However, resistance to single-agent treatment has been reported and therapies that improve the response duration are urgently required. We studied the preclinical combination of lorlatinib with chemotherapy, or with the MDM2 inhibitor, idasanutlin, as recent data have suggested that ALK inhibitor resistance can be overcome through activation of the p53-MDM2 pathway. Experimental Design: We compared different ALK inhibitors in preclinical models prior to evaluating lorlatinib in combination with chemotherapy or idasanutlin. We developed a triple chemotherapy (CAV: cyclophosphamide, doxorubicin, and vincristine) in vivo dosing schedule and applied this to both neuroblastoma genetically engineered mouse models (GEMM) and patient-derived xenografts (PDX). Results: Lorlatinib in combination with chemotherapy was synergistic in immunocompetent neuroblastoma GEMM. Significant growth inhibition in response to lorlatinib was only observed in the ALK-amplified PDX model with high ALK expression. In this PDX, lorlatinib combined with idasanutlin resulted in complete tumor regression and significantly delayed tumor regrowth. Conclusions: In our preclinical neuroblastoma models, high ALK expression was associated with lorlatinib response alone or in combination with either chemotherapy or idasanutlin. The synergy between MDM2 and ALK inhibition warrants further evaluation of this combination as a potential clinical approach for children with neuroblastoma.

Osteosarcoma is a recalcitrant bone malignancy with poor responsiveness to treatments; therefore, new chemotherapeutic compounds are needed. Sulforaphane (SFN) has been considered a promising chemotherapeutic compound for several types of tumors by inducing apoptosis and cytostasis, but its effects (e.g., genotoxicity) in osteosarcoma cells remains exploratory. In this work, the MG-63 osteosarcoma cell line was exposed to SFN up to 20 μM for 24 and 48 h. SFN induced G₂/M phase arrest and decreased nuclear division index, associated with disruption of cytoskeletal organization. Noteworthy, SFN induced a transcriptome response supportive of G₂/M phase arrest, namely a decrease in Chk1- and Cdc25C-encoding transcripts, and an increase in Cdk1-encoding transcripts. After 48-h exposure, SFN at a dietary concentration (5 μM) contributed to genomic instability in the MG-63 cells as confirmed by increased number of DNA breaks, clastogenicity, and nuclear and mitotic abnormalities. The increased formation of nucleoplasmic bridges, micronuclei, and apoptotic cells positively correlated with loss of viability. These results suggest that genotoxic damage is an important step for SFN-induced cytotoxicity in MG-63 cells. In conclusion, SFN shows potential to induce genotoxic damage at low concentrations and such potential deserves further investigation in other tumor cell types.

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 Pediatric Preclinical Proof-of-concept Platform (IMI2 ITCC-P4) for further exploitation. This PDX biobank of unique recurrent childhood cancers provides an essential support for basic and translational research and treatments development in advanced pediatric malignancies.

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 antitumoral 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 colocalized in keratin tumor niches. Significance: Novel individual biomarkers are needed to guide therapeutic decisions for patients with head and neck cancer. We report for the first time, granulomas of TREM2-expressing multinucleated giant macrophages in keratin-rich tumor niches, as a biomarker of favorable prognosis and developed a deep-learning model to automate its quantification on routinely stained pathological slides.