Distinct Biomarker Profiles and TCR Sequence Diversity Characterize the Response to PD-L1 Blockade in a Mouse Melanoma Model.

Only a subset of patients responds to immune checkpoint blockade (ICB) in melanoma. A preclinical model recapitulating the clinical activity of ICB would provide a valuable platform for mechanistic studies. We used melanoma tumors arising from an Hgftg;Cdk4R24C/R24C genetically engineered mouse (GEM) model to evaluate the efficacy of an anti-mouse PD-L1 antibody similar to the anti-human PD-L1 antibodies durvalumab and atezolizumab. Consistent with clinical observations for ICB in melanoma, anti-PD-L1 treatment elicited complete and durable response in a subset of melanoma-bearing mice. We also observed tumor growth delay or regression followed by recurrence. For early treatment assessment, we analyzed gene expression profiles, T-cell infiltration, and T-cell receptor (TCR) signatures in regressing tumors compared with tumors exhibiting no response to anti-PD-L1 treatment. We found that CD8+ T-cell tumor infiltration corresponded to response to treatment, and that anti-PD-L1 gene signature response indicated an increase in antigen processing and presentation, cytokine-cytokine receptor interaction, and natural killer cell-mediated cytotoxicity. TCR sequence data suggest that an anti-PD-L1-mediated melanoma regression response requires not only an expansion of the TCR repertoire that is unique to individual mice, but also tumor access to the appropriate TCRs. Thus, this melanoma model recapitulated the variable response to ICB observed in patients and exhibited biomarkers that differentiate between early response and resistance to treatment, providing a valuable platform for prediction of successful immunotherapy. IMPLICATIONS: Our melanoma model recapitulates the variable response to anti-PD-L1 observed in patients and exhibits biomarkers that characterize early antibody response, including expansion of the TCR repertoire.

Multimodel preclinical platform predicts clinical response of melanoma to immunotherapy.

Although immunotherapy has revolutionized cancer treatment, only a subset of patients demonstrate durable clinical benefit. Definitive predictive biomarkers and targets to overcome resistance remain unidentified, underscoring the urgency to develop reliable immunocompetent models for mechanistic assessment. Here we characterize a panel of syngeneic mouse models, representing a variety of molecular and phenotypic subtypes of human melanomas and exhibiting their diverse range of responses to immune checkpoint blockade (ICB). Comparative analysis of genomic, transcriptomic and tumor-infiltrating immune cell profiles demonstrated alignment with clinical observations and validated the correlation of T cell dysfunction and exclusion programs with resistance. Notably, genome-wide expression analysis uncovered a melanocytic plasticity signature predictive of patient outcome in response to ICB, suggesting that the multipotency and differentiation status of melanoma can determine ICB benefit. Our comparative preclinical platform recapitulates melanoma clinical behavior and can be employed to identify mechanisms and treatment strategies to improve patient care.

A preclinical orthotopic model for glioblastoma recapitulates key features of human tumors and demonstrates sensitivity to a combination of MEK and PI3K pathway inhibitors.

Current therapies for glioblastoma multiforme (GBM), the highest grade malignant brain tumor, are mostly ineffective, and better preclinical model systems are needed to increase the successful translation of drug discovery efforts into the clinic. Previous work describes a genetically engineered mouse (GEM) model that contains perturbations in the most frequently dysregulated networks in GBM (driven by RB, KRAS and/or PI3K signaling and PTEN) that induce development of Grade IV astrocytoma with properties of the human disease. Here, we developed and characterized an orthotopic mouse model derived from the GEM that retains the features of the GEM model in an immunocompetent background; however, this model is also tractable and efficient for preclinical evaluation of candidate therapeutic regimens. Orthotopic brain tumors are highly proliferative, invasive and vascular, and express histology markers characteristic of human GBM. Primary tumor cells were examined for sensitivity to chemotherapeutics and targeted drugs. PI3K and MAPK pathway inhibitors, when used as single agents, inhibited cell proliferation but did not result in significant apoptosis. However, in combination, these inhibitors resulted in a substantial increase in cell death. Moreover, these findings translated into the in vivo orthotopic model: PI3K or MAPK inhibitor treatment regimens resulted in incomplete pathway suppression and feedback loops, whereas dual treatment delayed tumor growth through increased apoptosis and decreased tumor cell proliferation. Analysis of downstream pathway components revealed a cooperative effect on target downregulation. These concordant results, together with the morphologic similarities to the human GBM disease characteristics of the model, validate it as a new platform for the evaluation of GBM treatment.

Temporal molecular and biological assessment of an erlotinib-resistant lung adenocarcinoma model reveals markers of tumor progression and treatment response.

Patients with lung cancer with activating mutations in the EGF receptor (EGFR) kinase, who are treated long-term with tyrosine kinase inhibitors (TKI), often develop secondary mutations in EGFR associated with resistance. Mice engineered to develop lung adenocarcinomas driven by the human EGFR T790M resistance mutation are similarly resistant to the EGFR TKI erlotinib. By tumor volume endpoint analysis, these mouse tumors respond to BIBW 2992 (an irreversible EGFR/HER2 TKI) and rapamycin combination therapy. To correlate EGFR-driven changes in the lung with response to drug treatment, we conducted an integrative analysis of global transcriptome and metabolite profiling compared with quantitative imaging and histopathology at several time points during tumor progression and treatment. Responses to single-drug treatments were temporary, whereas combination therapy elicited a sustained response. During tumor development, metabolomic signatures indicated a shift to high anabolic activity and suppression of antitumor programs with 11 metabolites consistently present in both lung tissue and blood. Combination drug treatment reversed many of the molecular changes found in tumored lung. Data integration linking cancer signaling networks with metabolic activity identified key pathways such as glutamine and glutathione metabolism that signified response to single or dual treatments. Results from combination drug treatment suggest that metabolic transcriptional control through C-MYC and SREBP, as well as ELK1, NRF1, and NRF2, depends on both EGFR and mTORC1 signaling. Our findings establish the importance of kinetic therapeutic studies in preclinical assessment and provide in vivo evidence that TKI-mediated antiproliferative effects also manifest in specific metabolic regulation.