Prediction of Hepatocellular Carcinoma Response to Transcatheter Arterial Chemoembolization: A Real-World Study Based on Non-Contrast Computed Tomography Radiomics and General Image Features.

OBJECTIVE: To construct a predictive model of short-term response and overall survival for transcatheter arterial chemoembolization (TACE) treatment in hepatocellular carcinoma (HCC) patients based on non-contrast computed tomography (NC-CT) radiomics and clinical features. METHODS: Ninety-four HCC patients who underwent CT scanning 1 week before the first TACE treatment were retrospectively recruited and divided randomly into a training group (n = 47) and a validation group (n = 47). NC-CT radiomics data were extracted using MaZda software, and the compound model was calculated from radiomics and clinical features by logistic regression. The performance of the different models was compared by examining the area under the receiver operating characteristic curve (AUC). The prediction of prognosis was evaluated using survival analysis. RESULTS: Thirty NC-CT radiomic features were extracted and analyzed. The compound model was formed using four NC-CT run-length matrix (RLM) features and general image features, which included the maximum diameter (cm) of the tumor and the number of tumors (n). The AUCs of the model for TACE response were 0.840 and 0.815, whereas the AUCs of the six-and-twelve grade were 0.754 and 0.750 in the training and validation groups, respectively. HCC patients were divided into two groups using the cutoff value of the model: a group in which the TACE-response led to good survival and a group in which TACE-nonresponse caused poor prognosis. CONCLUSION: Radiomic features from NC-CT predicted TACE-response. The compound model generated by NC-CT radiomics and clinical features is effective and directly predicts TACE-response and overall survival. The model may be used repeatedly and is easy to operate.

TELO2 induced progression of colorectal cancer by binding with RICTOR through mTORC2.

Colorectal cancer (CRC) is a common cancer worldwide, and its treatment strategies are limited. The underlying mechanism of CRC progression remains to be determined. Telomere maintenance 2 (TELO2) is a mTOR­interacting protein. Both the role and molecular mechanism of TELO2 in cancer progression remain unknown. In this study, the gene expression database of normal and tumor tissue, in addition to western blot analysis, and immunohistochemistry (IHC) were used to determine the expression and location of TELO2 in CRC and normal tissues. Clinical features of a tissue array were collected and analyzed. WST­1, soft agar, flow cytometry, wound healing, and invasion assays were employed to verify the role of TELO2 in the growth, cell cycle, migration, and invasion of CRC cells. The correlation between TELO2 and RICTOR (rapamycin­insensitive companion of mTOR) was analyzed by bioinformatics, IHC, and immunoprecipitation. Normal and serum­deprived cells were collected to detect the protein level of TELO2 and its downstream effectors. The results revealed that TELO2 was significantly upregulated in CRC, and TELO2 inhibition significantly restrained the growth, cell cycle, and metastasis of CRC cells. TELO2 overexpression correlated with age, lymph node metastasis, and TNM stage of CRC patients. In addition, TELO2 was positively correlated with RICTOR in CRC and induced tumor progression mainly via RICTOR with serum in culture. RICTOR induced the degradation of TELO2 upon serum deprivation in an mTOR­independent manner. These findings indicate that TELO2 promotes tumor progression via RICTOR in a serum­dependent manner, which may be a potential therapeutic target for CRC.