Proteomic Characterization of Head and Neck Cancer Patient-Derived Xenografts

Abstract

Despite advances in treatment approaches for head and neck squamous cell carcinoma (HNSCC), survival rates have remained stagnant due to the paucity of preclinical models that accurately reflect the human tumor. Patient-derived xenografts (PDX) are an emerging model system where patient tumors are implanted directly into mice. Increased understanding of the application and limitations of PDXs will facilitate their rational use. Studies to date have not reported protein profiles of PDXs. Therefore, we developed a large cohort of HNSCC PDXs and found that tumor take rate was not influenced by the clinical, pathologic, or processing features. Protein expression profiles, from a subset of the PDXs, were characterized by reverse-phase protein array and the data was compared with The Cancer Genome Atlas HNSCC data. Cluster analysis revealed that HNSCC PDXs were more similar to primary HNSCC than to any other tumor type. Interestingly, while a significant fraction of proteins were expressed similarly in both primary HNSCC and PDXs, a subset of proteins/phosphoproteins were expressed at higher (or lower) levels in PDXs compared with primary HNSCC. These findings indicate that the proteome is generally conserved in PDXs, but mechanisms for both positive and negative model selection and/or differences in the stromal components exist.

Implications: Proteomic characterization of HNSCC PDXs demonstrates potential drivers for model selection and provides a framework for improved utilization of this expanding model system.

Figure 1. HNSCC PDXs cluster with HNSCC patient tumors

A) RPPA data from 4778 specimens in the TCPA database comprising 14 different types of cancer (GBM, OVCA, LUAD, LUSC, BRCA, KIRC, UCEC, COAD, Gastric, HNSC, Melanoma, Thyroid, BLCA, Prostate, LGG) were compared to 13 HNSCC PDX specimens by unsupervised clustering. A total of 190 proteins were utilized for this comparison. HNSCC is depicted in red, PDX in green, other tumor types are shown in light gray. B) Magnification of the sub-branch containing the primary HNSCC region of the cluster.

Figure 2. HNSCC PDXs cluster together when compared to HNSCC alone

A) 173 HNSCC specimens and 12 HNSCC PDX specimens in the major HNSCC sub-branch cluster from Figure 1B. The three major sub-branches are denoted (numbers 1–3). A total of 190 proteins for each specimen were analyzed. B) Clustering analysis of 76 proteins expressed at similar levels in both primary HNSCC and HNSCC PDXs. T-test was applied to compare these 173 HNSCC and 12 PDX specimens. A false discovery rate > 0.05 was deemed as not significantly different. C) A more conservative p-value adjustment was used (Bonferroni Correction) and the adjusted p-value < 0.05 was applied to identify differentially expressed proteins (n=64).

Figure 2. HNSCC PDXs cluster together when compared to HNSCC alone

A) 173 HNSCC specimens and 12 HNSCC PDX specimens in the major HNSCC sub-branch cluster from Figure 1B. The three major sub-branches are denoted (numbers 1–3). A total of 190 proteins for each specimen were analyzed. B) Clustering analysis of 76 proteins expressed at similar levels in both primary HNSCC and HNSCC PDXs. T-test was applied to compare these 173 HNSCC and 12 PDX specimens. A false discovery rate > 0.05 was deemed as not significantly different. C) A more conservative p-value adjustment was used (Bonferroni Correction) and the adjusted p-value < 0.05 was applied to identify differentially expressed proteins (n=64).

Figure 2. HNSCC PDXs cluster together when compared to HNSCC alone

A) 173 HNSCC specimens and 12 HNSCC PDX specimens in the major HNSCC sub-branch cluster from Figure 1B. The three major sub-branches are denoted (numbers 1–3). A total of 190 proteins for each specimen were analyzed. B) Clustering analysis of 76 proteins expressed at similar levels in both primary HNSCC and HNSCC PDXs. T-test was applied to compare these 173 HNSCC and 12 PDX specimens. A false discovery rate > 0.05 was deemed as not significantly different. C) A more conservative p-value adjustment was used (Bonferroni Correction) and the adjusted p-value < 0.05 was applied to identify differentially expressed proteins (n=64).

Figure 3. Conserved and differentially expressed proteins in major HNSCC signaling pathways

Representative differences and similarities between HNSCC PDXs and primary human tumors are depicted in cell growth and apoptosis pathways. Proteins that were not significantly different between HNSCC PDXs and human tumors are depicted in green (subset of the n=76 proteins). Proteins that were significantly different between HNSCC PDXs and human tumors are depicted in red (subset of the n=64 proteins).

Figure 4. HNSCC PDX protein expression clustered by cancer hallmarks is different between positive and negative selection model proteins

A) Proteins that are expressed at different levels in HNSCC PDXs compared to primary HNSCC were categorized according to the hallmarks of cancer (31). B) Proteins that were negatively selected in HNSCC PDXs (lower expression in PDXs compared to primary HNSCC) were categorized by the hallmarks of cancer. C) Proteins that were positively selected in PDXs (high expression in PDXs compared to primary HNSCC) were categorized by the hallmarks of cancer.