The importance of developing effective strategies for investigating mediastinal lymph-node metastases in non-small cell lung cancers is increasingly emphasized. It is because the precise detection of this metastatic disease is critical for optimal surgical intervention and treatment for patients with lung cancer. Existing medical image analysis is of limited power for mediastinal lymph-node staging on computed tomography (CT). Motivated by the radiomics hypothesis, this paper explored deep-learning, texture features and their combinations to ascertain subtle difference between malignant and benign mediastinal lymph nodes on CT. The radiomics-based results are found to be promising for differentiating malignant from benign mediastinal lymph nodes of patients with lung cancer.