Anlotinib, a novel small molecular tyrosine kinase inhibitor, suppresses growth and metastasis via dual blockade of VEGFR2 and MET in osteosarcoma.

Osteosarcoma is the most common primary malignant bone tumor in children and adolescents, with highly aggressive behavior and early systemic metastasis. The survival rates for osteosarcoma remain unchanged over the past two decades. Studies aiming to find new or alternative therapies for patients with refractory osteosarcoma are urgently needed. Anlotinib, a novel multi-targeted tyrosine kinase inhibitor (TKI), has exhibited encouraging clinical activity in NSLCC and soft tissue sarcoma, whereas its effect on osteosarcoma has not been studied. In our study, we investigated the anti-tumor activity and underlying mechanism of anlotinib in osteosarcoma. Various in vitro and in vivo models of human osteosarcoma were used to determine the anti-proliferative, anti-angiogenesis and anti-metastasis efficacy of anlotinib. Our results showed that anlotinib suppressed tumor growth and increased the chemo-sensitivity of osteosarcoma. In addition, anlotinib inhibited migration and invasion in osteosarcoma cells. Furthermore, in order to explore the anti-tumor mechanism of anlotinib, phospho-RTK antibody arrays were performed. These analyses confirmed that anlotinib suppressed the phosphorylation of MET, VEGFR2 and the downstream signaling pathway activation. Moreover, we demonstrated that anlotinib blocked hepatocyte growth factor (HGF)-induced cell migration, invasion and VEGF-induced angiogenesis. Notably, a 143B-Luc orthotopic osteosarcoma model further showed that anlotinib significantly inhibited growth and lung metastasis of implanted tumor cells. Our preclinical work indicates that anlotinib acts as a novel inhibitor of VEGFR2 and MET that blocks tumorigenesis in osteosarcoma, which could be translated into future clinical trials.

A MRI-based radiomics model for predicting the response to anlotinb combined with temozolomide in recurrent malignant glioma patients.

OBJECTIVE: Anlotinib is a multitarget anti-angiogenic drug that combined with temozolomide (TMZ) can effectively prolongs the overall survival (OS) of recurrent malignant glioma(rMG),but some patients do not respond to anlotinib combined with TMZ. These patients were associated with a worse prognosis and lack effective identification methods. Therefore, it is necessary to differentiate patients who may have good response to anlotinb in combination with TMZ from those who are not, in order to provide personalized targeted therapies. METHODS: Fifty three rMG patients (42 in training cohort and 11 in testing cohort) receiving anlotinib combined with TMZ were enrolled. A total of 3668 radiomics features were extracted from the recurrent MRI images. Radiomics features are reduced and filtered by hypothesis testing and Least Absolute Shrinkage And Selection (LASSO) regression. Eight machine learning models construct the radiomics model, and then screen out the optimal model. The performance of the model was assessed by its discrimination, calibration, and clinical usefulness with validation. RESULTS: Fifty three patients with rMG were enrolled in our study. Thirty four patients displayed effective treatment response, showed a higher survival benefits than non-response group, the median progression-free survival(PFS) was 8.53 months versus 5.33 months (p = 0.06) and the median OS was 19.9 months and 7.33 months (p = 0.029), respectively. Three radiomics features were incorporated into the model construction as final variables after LASSO regression analysis. In testing cohort, Logistic Regression (LR) model has the best performance with an Area Under the Curve (AUC) of 0.93 compared with other models, which can effectively predict the response of rMG patients to anlotinib in combination with TMZ. The calibration curve confirmed the agreement between the observed actual and prediction probability. Within the reasonable threshold probability range (0.38-0.88), the radiomics model shows good clinical utility. CONCLUSIONS: The above-described radiomics model performed well, which can serve as a clinical tool for individualized prediction of the response to anlotinb combined with TMZ in rMG patients.

Anlotinib suppresses metastasis and multidrug resistance via dual blockade of MET/ABCB1 in colorectal carcinoma cells.

Anlotinib, a highly selective multi-targeted tyrosine kinase inhibitor (TKI) has therapeutic effects on non-small-cell lung cancer (NSCLC). In this study, the anti-tumor activity and molecular mechanism of anlotinib in metastatic colorectal cancer (mCRC) was explored. The anti-angiogenesis, anti-metastasis, anti-proliferative, and anti-multidrug resistance efficacy of anlotinib were analyzed by using in vitro and in vivo models of human CRC cells. The results indicated that anlotinib boosted chemo-sensitivity of CRC cells, and restrained its proliferation. Besides the suppression of the MET signaling pathway, anlotinib also inhibited invasion and migration of CRC cells. Furthermore, anlotinib prevented VEGF-induced angiogenesis, N-cadherin (CDH2)-induced cell migration, and reversed ATP-binding cassette subfamily B member 1 (ABCB1) -mediated CRC multidrug resistance in CRC. The CRC liver metastasis and subcutaneously implanted xenograft model testified that anlotinib could inhibit proliferation and liver metastasis in CRC cells. Such an observation suggested that a combination of anlotinib with anti-cancer drugs could attenuate angiogenesis, metastasis, proliferative, and multidrug resistance, which constitutes a novel treatment strategy for CRC patients with metastasis.