The low rate of approval of novel anti-cancer agents underscores the need for better preclinical models of therapeutic response as neither xenografts nor early-generation genetically engineered mouse models (GEMMs) reliably predict human clinical outcomes. Whereas recent, sporadic GEMMs emulate many aspects of their human disease counterpart more closely, their ability to predict clinical therapeutic responses has never been tested systematically. We evaluated the utility of two state-of-the-art, mutant Kras-driven GEMMs--one of non-small-cell lung carcinoma and another of pancreatic adenocarcinoma--by assessing responses to existing standard-of-care chemotherapeutics, and subsequently in combination with EGFR and VEGF inhibitors. Standard clinical endpoints were modeled to evaluate efficacy, including overall survival and progression-free survival using noninvasive imaging modalities. Comparisons with corresponding clinical trials indicate that these GEMMs model human responses well, and lay the foundation for the use of validated GEMMs in predicting outcome and interrogating mechanisms of therapeutic response and resistance.

Resistance to anti-angiogenic therapy can occur via several potential mechanisms. Unexpectedly, recent studies showed that short-term inhibition of either VEGF or VEGFR enhanced tumour invasiveness and metastatic spread in preclinical models. In an effort to evaluate the translational relevance of these findings, we examined the consequences of long-term anti-VEGF monoclonal antibody therapy in several well-validated genetically engineered mouse tumour models of either neuroendocrine or epithelial origin. Anti-VEGF therapy decreased tumour burden and increased overall survival, either as a single agent or in combination with chemotherapy, in all four models examined. Importantly, neither short- nor long-term exposure to anti-VEGF therapy altered the incidence of metastasis in any of these autochthonous models, consistent with retrospective analyses of clinical trials. In contrast, we observed that sunitinib treatment recapitulated previously reported effects on tumour invasiveness and metastasis in a pancreatic neuroendocrine tumour (PNET) model. Consistent with these results, sunitinib treatment resulted in an up-regulation of the hypoxia marker GLUT1 in PNETs, whereas anti-VEGF did not. These results indicate that anti-VEGF mediates anti-tumour effects and therapeutic benefits without a paradoxical increase in metastasis. Moreover, these data underscore the concept that drugs targeting VEGF ligands and receptors may affect tumour metastasis in a context-dependent manner and are mechanistically distinct from one another.

Genetically engineered mouse models (GEMMs) of lung cancer closely recapitulate the human disease but suffer from the difficulty of evaluating tumor growth by conventional methods. Herein, a novel automated image analysis method for estimating the lung tumor burden from in vivo micro-computed tomography (micro-CT) data is described. The proposed tumor burden metric is the segmented soft tissue volume contained within a chest space region of interest, excluding an estimate of the heart volume. The method was validated by comparison with previously published manual analysis methods and applied in two therapeutic studies in a mutant K-ras GEMM of non–small cell lung carcinoma. Mice were imaged by micro-CT pre-treatment and stratified into four treatment groups: an antibody inhibiting vascular endothelial growth factor (anti-VEGF), chemotherapy, combination of anti-VEGF and chemotherapy, or control antibody. In the first study, post-treatment imaging was performed 4 weeks later. In the second study, mice were scanned serially on a high-throughput scanner every 2 weeks for 8 weeks during treatment. In both studies, the automated tumor burden estimates were well correlated with manual metrics (r value range: 0.83-0.93, P < .0001) and showed a similar, significant reduction in tumor growth in mice treated with anti-VEGF alone or in combination with chemotherapy. Given the fully automated nature of this technique, the proposed analysis method can provide a valuable tool in preclinical drug research for screening and randomizing animals into treatment groups and evaluating treatment efficacy in mouse models of lung cancer in a highly robust and efficient manner.

The phosphatidylinositol 3 kinase (PI3K)/AKT/ mechanistic target of rapamycin (mTOR) signaling pathway is a major regulator of tumor cell growth, proliferation and survival. Dysregulation of the PI3K/AKT/mTOR signaling pathway through multiple different mechanisms has been described in solid tumor malignancies, including activating and transforming mutations and amplification of PIK3CA, that encodes the p110alpha subunit of PI3K. Indeed, PIK3CA hotspot mutations are highly prevalent in breast cancer, occurring in approximately 40% of HR+ tumors. The clinical candidate GDC-0077 is a potent inhibitor of PI3Kalpha (IC50 = 0.038 nM) and exerts its activity by binding to the ATP binding site of PI3K, thereby inhibiting the phosphorylation of PIP2 to PIP3. Biochemically, GDC-0077 is &gt;300-fold more selective for PI3Kalpha over the other class I PI3K isoforms (beta, delta, and gamma) and &gt;2000-fold more selective over PIK family members. Furthermore, GDC-0077 is more selective for mutant versus wild-type PI3Kalpha in cell based assays. The improved biochemical selectivity of GDC-0077 relative to PI3Kdelta translated in human CD69+ B-cells, which are primarily dependent on PI3Kdelta for proliferation and survival, and were more sensitive (based on reduction of cell number) to the PI3Kalpha/delta selective inhibitor taselisib (GDC-0032) than to GDC-0077. Mechanism of action (MOA) studies indicate that GDC-0077 selectively degrades mutant PI3Kalpha in a proteasome-dependent fashion resulting in reduction of PI3K pathway activity biomarkers such as pAKT and pPRAS40, inhibition of cell proliferation, and increased apoptosis in human PIK3CA-mutant breast cancer cell lines to a greater extent when compared to PIK3CA wild-type cells. In vivo, oral daily treatment of patient-derived PIK3CA-mutant breast cancer xenograft models with GDC-0077 resulted in tumor regressions, induction of apoptosis, and a reduction of pAKT, pPRAS40, and pS6RP in a dose-dependent fashion. In vivo efficacy in a PIK3CA-mutant human breast cancer xenograft model was also improved when GDC-0077 was combined with therapies for hormone-receptor positive (HR+) breast cancer such as anti-estrogens (fulvestrant) or a CDK4/6 inhibitor (palbociclib). Collectively, preclinical studies provide rationale for evaluating GDC-0077, a PI3Kalpha selective inhibitor that degrades mutant p110alpha protein, as a single agent and in combination with endocrine and targeted therapies that may provide additional benefit to patients with locally advanced or metastatic hormone receptor+ breast cancers that harbor PIK3CA mutations. Citation Format: Hong R, Edgar K, Song K, Steven S, Young A, Hamilton P, Arrazate A, De La Cruz C, Chan C, Pang J, Salphati L, Belvin M, Nannini M, Staben S, Friedman L, Sampath D. GDC-0077 is a selective PI3Kalpha inhibitor that demonstrates robust efficacy in PIK3CA mutant breast cancer models as a single agent and in combination with standard of care therapies [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr PD4-14.

The effect of anti-angiogenic agents on tumor oxygenation has been in question for a number of years, where both increases and decreases in tumor pO2 have been observed. This dichotomy in results may be explained by the role of vessel normalization in the response of tumors to anti-angiogenic therapy, where anti-angiogenic therapies may initially improve both the structure and the function of tumor vessels, but more sustained or potent anti-angiogenic treatments will produce an anti-vascular response, producing a more hypoxic environment. The first goal of this study was to employ multispectral (MS) 19F–MRI to noninvasively quantify viable tumor pO2 and evaluate the ability of a high dose of an antibody to vascular endothelial growth factor (VEGF) to produce a strong and prolonged anti-vascular response that results in significant tumor hypoxia. The second goal of this study was to target the anti-VEGF induced hypoxic tumor micro-environment with an agent, tirapazamine (TPZ), which has been designed to target hypoxic regions of tumors. These goals have been successfully met, where an antibody that blocks both murine and human VEGF-A (B20.4.1.1) was found by MS 19F–MRI to produce a strong anti-vascular response and reduce viable tumor pO2 in an HM-7 xenograft model. TPZ was then employed to target the anti-VEGF-induced hypoxic region. The combination of anti-VEGF and TPZ strongly suppressed HM-7 tumor growth and was superior to control and both monotherapies. This study provides evidence that clinical trials combining anti-vascular agents with hypoxia-activated prodrugs should be considered to improved efficacy in cancer patients.