A patient tumor transplant model of squamous cell cancer identifies PI3K inhibitors as candidate therapeutics in defined molecular bins

Abstract

Targeted therapy development in head and neck squamous cell carcinoma (HNSCC) is challenging given the rarity of activating mutations. Additionally, HNSCC incidence is increasing related to human papillomavirus (HPV). We sought to develop an in vivo model derived from patients reflecting the evolving HNSCC epidemiologic landscape, and use it to identify new therapies. Primary and relapsed tumors from HNSCC patients, both HPV+ and HPV-, were implanted on mice, giving rise to 25 strains. Resulting xenografts were characterized by detecting key mutations, measuring protein expression by IHC and gene expression/pathway analysis by mRNA-sequencing. Drug efficacy studies were run with representative xenografts using the approved drug cetuximab as well as the new PI3K inhibitor PX-866. Tumors maintained their original morphology, genetic profiles and drug susceptibilities through serial passaging. The genetic makeup of these tumors was consistent with known frequencies of TP53, PI3KCA, NOTCH1 and NOTCH2 mutations. Because the EGFR inhibitor cetuximab is a standard HNSCC therapy, we tested its efficacy and observed a wide spectrum of efficacy. Cetuximab-resistant strains had higher PI3K/Akt pathway gene expression and protein activation than cetuximab-sensitive strains. The PI3K inhibitor PX-866 had anti-tumor efficacy in HNSCC models with PIK3CA alterations. Finally, PI3K inhibition was effective in two cases with NOTCH1 inactivating mutations. In summary, we have developed an HNSCC model covering its clinical spectrum whose major genetic alterations and susceptibility to anticancer agents represent contemporary HNSCC. This model enables to prospectively test therapeutic-oriented hypotheses leading to personalized medicine.

Keywords: EGFR; Head and neck cancer; Human papillomavirus; NOTCH1; PI3K; Xenografts.

Figure 1

Assessment of engrafted tumors, A. Schema representing the model. For implantation we used our standard technique (Jimeno et al., 2009; Rubio‐Viqueira et al., 2006), which maintains a narrow control on size and number of pieces of the first (F1) implantation. The number of pieces implanted (6, 8, and 10 tumor pieces in 9%, 22%, and 69% of cases) in F1 did not influence the success of engraftment. B. Orthotopic tumors with locoregional nodes (in the base of tongue [BOT] model the neck is dissected for clarity). Nodes from mice with orthotopic tumors grew >5 mm, compared with <1 mm in normal nodes. Immunohistochemistry (x40; bar 50 μM) with human EGFR and cytokeratin 5, mouse CD45, and dual FISH labeling of mouse cot (green) and humand cot (red) on neck nodes from mice that never had a human tumor (above), and a floor‐of‐mouth (FOM) implantation (below). C. Paired microphotographs (x20; bar 100 μM) of F0 and F2 hematoxilyn‐eosin and EGFR staining of three cases with well (above), moderate (middle) and poor (lower) degree of squamous differentiation. The tumors propagated on mice maintained these features and the EGFR staining across the spectrum. D. All cases showed EGFR positivity by immunohistochemistry (IHC), whose intensity, percentage and H‐score ranged from 1 to 3 (average±SD, 2.5 ± 0.6), 50%–100% (89% ± 18%), and 100 to 300 (226 ± 71). The plot of the correlation between the F0 and F2 H‐score for EGFR staining shows a high degree of correlation (R2 = 0.91, P < 0.0001). Although there were divergences in the H‐score in 9 of 25 paired samples, all were <20% and all cases were classified in the same category. E. Gene expression variations between F0 vs F2 vs F4 generations were compared for the CUHN014 and CUHN022 cases using the expression value of genes that significantly mapped to the human genome in at least one case and/or generation. The greatest variation for both cases was between the F0 patient sample and the F2, with stabilization further. Expression nearly completely stabilized once established on mice with R‐squared values for F2 vs F4 of 0.938 and 0.959 for CUHN014 and CUHN022.

Figure 2

Mutation profiling, A. Positions of previously documented and undocumented (*), nonsense (red) and missense (black) mutations in PI3KCA, NOTCH1, and TP53. Fifty percent of the TP53 nonsense mutations occurred upstream of the DNA binding domain. Two mutually exclusive mutations occurred at a higher frequency. A G > T transversion resulting in G245V, and a C > T transition resulting in R282W were observed in 17% of TP53 mutants. Regarding NOTCH1 mutations, previous studies report putative loss of function mutations disrupting the ligand‐binding EGF‐like repeats in the N‐terminal extracellular domain of the receptor at frequencies between 11 and 15%; our observed rate is higher, but this needs to be balanced with our smaller sample size. Interestingly, in CUHN041 the two alleles have different mutations within the same codon producing a homozygous P1770F amino acid change. Mutations in NOTCH1 HD are activating in T acute lymphocityc leukemia (T‐ALL) (Malecki et al., 2006) and lung cancer (Westhoff et al., 2009). However, a R1608S mutation in the HD domain did not increase Notch1 activity in T‐ALL (Malecki et al., 2006), suggesting that the R1608 mutation in CUHN049 is possibly inactivating. B. Prevalence of NOTCH1 germline mutations in mutant xenografts. C. Samples hybridized with EGFR (red) and PI3KCA (green) FISH probes showed a wide spectrum of amplification. Insert: representative cell; –a: amplified; –na: not amplified. D. Schemata depicting tumors with key genetic alterations in TP53, PI3KCA, and NOTCH1.

Figure 3

Treatment efficacy of cetuximab, A. Eleven cases received weekly cetuximab infusions or vehicle, and showed a wide spectrum of efficacy. Seven cases had a growth reduction over 50% compared to untreated, and four had actual tumor shrinkage below baseline tumor size. These four were heterogeneous in their clinical profile (two primaries and two relapses; two FOTM, one tongue, one BOT) but all four were smokers and HPV−. The three cases with lowest susceptibility correspond to an SSCC with a KRAS mutation (CUHN016) and the only two HPV+ HNSCC cases (CUHN014 and CUHN022). The tumor line plot of the highest and lowest susceptible cases CUHN002 and CUHN016 are shown. B. Repeated treatment at different generations of susceptible, intermediate and resistant cases indicated stable response to cetuximab. C. The Western blot analyses evidenced that the level of baseline expression of EGFR, phospho‐EGFR, Akt, phospho‐Akt, MAPK, or phospho‐MAPK was not predictive of efficacy. Pharmacodynamic changes after therapy were also unrelated with susceptibility to cetuximab. As previously reported, HPV+ cases (CUHN014 and CUHN022) had higher baseline phospho‐Akt. Bars are normalized to untreated control in each case, with calculated standard error (SE).

Figure 4

Treatment efficacy with PI3K inhibition, A. PX‐866 is a pan‐isoform inhibitor of PI3K with IC50s of 39 ± 21 nM, 88 ± 27 nM, 124 ± 26 nM, and 183 ± 25 against PI3Kα, PI3Kβ, PI3Kδ, and PI3Kγ, respectively. Mice were dosed for 28 days, and a wide range of efficacy was documented. The tumor line plot of the highest and lowest susceptible cases CUHN027 and CUHN002 are shown. B. Phospho‐S6K was highest in CUHN026 and CUHN027, and phospho‐Akt in CUHN026, as expected given it is the only case with an activating PI3KCA mutation. Greater than 80% decreases in post‐therapy phospho‐Akt and phospho‐S6K were documented in the susceptible CUHN027 and CUHN026, indicating on‐target inhibition and underscoring their value as surrogates of driver pathway abrogation. In CUHN014 and CUHN022 phospho‐Akt decreases between 50 and 80% were evidenced. Micro‐photographs are x40; bar 50 μM. C. Western blot analyses confirmed the IHC findings; additionally phospho‐PI3K showed the highest decrease in CUHN026.

Figure 5

Core genes for cetuximab and PX‐866 susceptibility. Pathway enrichment analysis of cetuximab (above) and PX‐866 (below) from RNA‐seq according to susceptibility (sensitive vs. resistant). Red and green colors represent enrichment in sensitive and resistant group, respectively. Enrichment maps were abstracted from the pathways with P < 0.05 (GSEA analysis) by comparing RNA‐seq of sensitive vs. resistant models, and were manually adjusted to highlight the most relevant pathways for visualization purposes.