Cancer characterization using light backscattering spectroscopy and quantitative ultrasound: an ex vivo study on sarcoma subtypes.

Histological analysis is the gold standard method for cancer diagnosis. However, it is prone to subjectivity and sampling bias. In response to these limitations, we introduce a quantitative bimodal approach that aims to provide non-invasive guidance towards suspicious regions. Light backscattering spectroscopy and quantitative ultrasound techniques were combined to characterize two different bone tumor types from animal models: chondrosarcomas and osteosarcomas. Two different cell lines were used to induce osteosarcoma growth. Histological analyses were conducted to serve as references. Three ultrasound parameters and intensities of the light reflectance profiles showed significant differences between chondrosarcomas and osteosarcomas at the 5% level. Likewise, variations in the same biomarkers were reported for the two types of osteosarcoma, despite their similar morphology observed in the histological examinations. These observations show the sensitivity of our techniques in probing fine tissue properties. Secondly, the ultrasound spectral-based technique identified the mean size of chondrosarcoma cells and nuclei with relative errors of about 22% and 9% respectively. The optical equivalent technique correctly extracted scatterer size distributions that encompass nuclei and cells for chondrosarcomas and osteosarcomas ([Formula: see text] and [Formula: see text] respectively). The optical scattering contributions of nuclei were estimated at 52% for the chondrosarcomas and 69% for the osteosarcomas, probably indicating the abundant and the absent extracellular matrix respectively. Thus, the ultrasound and the optical methods brought complementary parameters. They successfully estimated morphological parameters at the cellular and the nuclear scales, making our bimodal technique promising for tumor characterization.

The TLR3 L412F polymorphism prevents TLR3-mediated tumor cell death induction in pediatric sarcomas.

Toll-like receptor 3 (TLR3) is a pattern recognition receptor mainly known for its role in innate immune response to infection. Indeed, binding of double-stranded RNA (dsRNA) to TLR3 triggers a pro-inflammatory cascade leading to cytokine release and immune cell activation. Its anti-tumoral potential has emerged progressively, associated with a direct impact on tumor cell death induction and with an indirect action on immune system reactivation. Accordingly, TLR3 agonists are currently being tested in clinical trials for several adult cancers. Meanwhile, TLR3 variants have been linked to auto-immune disorders, and as risk factors of viral infection and cancers. However, aside from neuroblastoma, TLR3 role in childhood cancers has not been evaluated. Here, by integrating public transcriptomic data of pediatric tumors, we unveil that high TLR3 expression is largely associated with a better prognosis in childhood sarcomas. Using osteosarcomas and rhabdomyosarcomas as models, we show that TLR3 efficiently drives tumor cell death in vitro and induces tumor regression in vivo. Interestingly, this anti-tumoral effect was lost in cells expressing the homozygous TLR3 L412F polymorphism, which is enriched in a rhabdomyosarcomas cohort. Thus, our results demonstrate the therapeutic potential associated with the targeting of TLR3 in pediatric sarcomas, but also the need to stratify patients eligible for this clinical approach with respect to the TLR3 variants expressed.