Development of a Fundamental Technology to Seek Drug Targets, and Its Application to Cancer Targeting Therapy

Abstract

Human epidermal growth factor receptor 2 (Her2)-targeting antibodies and anti-hormone therapy are eŠective for most breast cancer patients. However, such approaches are not viable with resistant cases or in triple-negative breast cancer (TNBC) patients, given the lack of Her2 and estrogen and progesterone receptors in these patients. Thus, new drug targets are urgently required. From this perspective, we searched for novel drug targets using proteomic analysis, and identiˆed Eph receptor A10 (EphA10), which is elevated in breast cancer cells as compared to normal breast tissue. Here, we evaluated the potential of EphA10 as a drug target by analyzing its protein expression proˆle/function in cancer cells, and then by using an anti-EphA10 antibody to treat EphA10-expressing tumor-bearing mice. Protein expression proˆle analysis showed that EphA10 was expressed in various breast cancer subtypes, including TNBCs, with no expression observed in normal tissues, apart from the testes. Moreover, functional analysis of the cancer cells revealed that ligand-dependent proliferation was observed in EphA10-expressed cancer cells. Thus, we developed our novel antiEphA10 antibody, which binds to EphA10 with high speciˆcity and a‹nity at the nanomolar level. Finally, therapeutic analysis indicated that tumor growth was signiˆcantly suppressed in the mAb-treated mice in a dose-dependent manner. These results suggest that the EphA10-targeting therapy may be a novel therapeutic option for the management of breast cancer, including in TNBCs which aren't currently treated with molecular-targeted agents. Consequently, we hope that theseˆndings will contribute to the development of a new targeting therapy for refractory breast cancer patients.

NIMA-related kinase 2 overexpression is associated with poor survival in cancer patients: a systematic review and meta-analysis

“…Epidemiological studies show that 14.1 million new cancer cases and 8.2 million cancer-related deaths occur annually worldwide, and these numbers are on the rise 2,3. Early diagnosis and prognosis prediction are helpful for choosing treatments for cancer patients, but traditional detection methods such as imaging techniques and biopsy have their limitations 4,5. Therefore, it is necessary to identify new biomarkers for early diagnosis and for predicting patients’ prognosis to improve the efficacy of cancer treatment.…”