Exploiting the immune landscape of HOXA9/WNT6-driven glioblastoma: opportunities for novel precision therapies

Glioblastoma (GBM) is a notoriously devastating malignant brain tumor, presenting remarkable intratumor heterogeneity. Despite aggressive treatments, it is universally fatal, with a median patient survival of only ~15 months, ranking 1st among all tumor types for average years of life lost. These poor clinical outcomes have not changed significantly for decades, highlighting an urgent unmet need for better and more rational precision therapies, and a more refined comprehension of this cancer, particularly taking advantage of innovative approaches that preserve spatial context information with (near-) single-cell resolution.
Considering the multiple lines of evidence suggesting that HOXA9 and WNT6 can modulate immune responses, and are attractive therapeutic targets due to their broad oncogenic roles in GBM, here we aim to study:
– how the HOXA9/WNT6 molecular axis affects the immune landscape of GBM, investigating patient samples with high-throughput approaches, including tissue spatial transcriptomics to preserve location context within the cellular heterogeneity of GBM, and single-cell gene expression and TCR-sequencing to identify clonotypic T cell signatures, both of which will support the discovery of new GBM biomarkers;
– the influence of HOXA9/WNT6 in the response of immunocompetent preclinical GBM models to immune checkpoint therapies, and understand how precision combination treatments with HOXA9/WNT6-targeting therapies may be valuable for GBM.
Our findings will portray the spatial transcriptomics and immune landscape driven by HOXA9 and WNT6 in GBM, identify novel combination therapies exploring key oncogenes and immune functions in GBM, and pinpoint novel clinical biomarkers that may guide and prioritize patient stratification to immuno- and combination-therapies.

Funding Agency

FCT, Portugal

Project Reference


Project Members

Main Project Outcomes

S. Queirós, “Right ventricular segmentation in multi-view cardiac MRI using a unified U-net model”, in E. Puyol Antón et al. (eds) Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge. STACOM 2021. Lecture Notes in Computer Science, vol 13131, pp. 287-295, Springer, Cham, 2022.

“Best Paper Award in the M&Ms-2 Challenge”, by M&Ms2 Challenge organizers and the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society.