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Updated: Jul 16, 2025
Therapy Testing in a Spheroid-based 3D Cell Culture Model for Head and Neck Squamous Cell Carcinoma
Published on: April 20, 2018
Deep spatial-omics analysis of Head & Neck carcinomas provides alternative therapeutic targets and rationale for
Andrew Causer1, Xiao Tan2, Xuehan Lu2
1Institute of Molecular Biology, The University of Queensland, Brisbane, QLD, Australia.
Abstract:
Immune checkpoint inhibitor (ICI) therapy has had limited success (<30%) in treating metastatic recurrent Head and Neck Oropharyngeal Squamous Cell Carcinomas (OPSCCs). We postulate that spatial determinants in the tumor play a critical role in cancer therapy outcomes. Here, we describe the case of a male patient diagnosed with p16+ OPSCC and extensive lung metastatic disease who failed Nivolumab and Pembrolizumab/Lenvatinib therapies. Using advanced integrative spatial proteogenomic analysis on the patient's recurrent OPSCC tumors we demonstrate that: (i) unbiased tissue clustering based on spatial transcriptomics (ST) successfully detected tumor cells and enabled the investigation of phenotypic traits such as proliferation or drug-resistance genes in the tumor's leading-edge and core; (ii) spatial proteomic imagining used in conjunction with ST (SpiCi, Spatial Proteomics inferred Cell identification) can resolve the profiling of tumor infiltrating immune cells, (iii) ST data allows for the discovery and ranking of clinically relevant alternative medicines based on their interaction with their matching ligand-receptor. Importantly, when the spatial profiles of ICI pre- and post-failure OPSCC tumors were compared, they exhibited highly similar PD-1/PD-L1low and VEGFAhigh expression, suggesting that these new tumors were not the product of ICI resistance but rather of Lenvatinib dose reduction due to complications. Our work establishes a path for incorporating spatial-omics in clinical settings to facilitate treatment personalization.
Insights
Immune checkpoint inhibitor therapy shows limited success for head and neck cancers. Spatial proteogenomic analysis reveals tumor characteristics influencing treatment response, paving the way for personalized medicine.
Area of Science:
- Oncology
- Immunotherapy
- Genomics
Background:
- Immune checkpoint inhibitor (ICI) therapy has limited efficacy (<30%) in metastatic recurrent Head and Neck Oropharyngeal Squamous Cell Carcinomas (OPSCCs).
- Spatial factors within tumors are hypothesized to critically influence cancer therapy outcomes.
- A case study of a patient with p16+ OPSCC and extensive lung metastases who failed Nivolumab and Pembrolizumab/Lenvatinib therapies is presented.
Purpose of the Study:
- To investigate the role of spatial determinants in treatment failure for OPSCC.
- To demonstrate the utility of integrative spatial proteogenomic analysis in understanding tumor biology and guiding personalized treatment strategies.
- To explore potential alternative therapeutic targets based on spatial transcriptomics data.
Main Methods:
- Integrative spatial proteogenomic analysis was performed on recurrent OPSCC tumor samples.
- Spatial transcriptomics (ST) was used for unbiased tissue clustering and identification of phenotypic traits (e.g., proliferation, drug resistance) in different tumor regions.
- Spatial proteomics imaging combined with ST (SpiCi) was employed to profile tumor-infiltrating immune cells.
Main Results:
- Spatial transcriptomics successfully identified tumor cells and enabled analysis of gene expression in the tumor's leading edge and core.
- SpiCi facilitated the profiling of tumor-infiltrating immune cells.
- ST data enabled the discovery and ranking of potential alternative medicines based on ligand-receptor interactions.
- Comparison of pre- and post-ICI failure OPSCC tumors revealed similar PD-1/PD-L1 low and VEGFA high expression, suggesting treatment failure was linked to Lenvatinib dose reduction rather than ICI resistance.
Conclusions:
- Spatial-omics analysis provides critical insights into tumor heterogeneity and its impact on therapeutic response.
- The findings support the integration of spatial-omics into clinical settings for personalized treatment of OPSCC.
- This approach can help identify non-responders to current therapies and suggest alternative treatment strategies.
