Leucine deprivation inhibits proliferation and induces apoptosis of human breast cancer cells via fatty acid synthase

Chemerin, a known chemoattractant, participates in multiple biological events. However, its role in cancer remains largely unknown. Chemerin expression was evaluated by real-time PCR, western blot and immunohistochemistry. Forced expression, RNAi, immunoprecipitation, etc. were used in function and mechanism study. Mouse models of extrahepatic and intrahepatic metastasis were employed to evaluate the therapeutic potential of chemerin. Chemerin expression was significantly downregulated in hepatocellular carcinoma, and associated with poor prognosis of HCC patients. Forced expression of chemerin inhibited in vitro migration, invasion and in vivo metastasis of HCC cells. Administration of chemerin effectively suppressed extrahepatic and intrahepatic metastases of HCC cells, resulting in prolonged survival of tumour-bearing nude mice. Chemerin upregulated expression and phosphatase activity of PTEN by interfering with PTEN–CMKLR1 interaction, leading to weakened ubiquitination of PTEN and decreased p-Akt (Ser473) level, which was responsible for suppressed migration, invasion and metastasis of HCC cells. Positive correlation between chemerin and PTEN, and reverse correlation between chemerin and p-Akt (Ser473) were also observed in HCC clinical samples and intrahepatic mouse model in vivo. Our study has revealed the suppressive role and therapeutic potential of chemerin in HCC metastasis, providing both a prognostic marker and drug candidate for HCC.

Background: Microsatellite instability (MSI) predetermines responses to adjuvant 5‐fluorouracil and immunotherapy in rectal cancer and serves as a prognostic biomarker for clinical outcomes. Our objective was to develop and validate a deep learning model that could preoperatively predict the MSI status of rectal cancer based on magnetic resonance images.Methods: This single‐center retrospective study included 491 rectal cancer patients with pathologically proven microsatellite status. Patients were randomly divided into the training/validation cohort (n = 395) and the testing cohort (n = 96). A clinical model using logistic regression was constructed to discriminate MSI status using only clinical factors. Based on a modified MobileNetV2 architecture, deep learning models were tested for the predictive ability of MSI status from magnetic resonance images, with or without integrating clinical factors.Results: The clinical model correctly classified 37.5% of MSI status in the testing cohort, with an AUC value of 0.573 (95% confidence interval [CI], 0.468 ~ 0.674). The pure imaging‐based model and the combined model correctly classified 75.0% and 85.4% of MSI status in the testing cohort, with AUC values of 0.820 (95% CI, 0.718 ~ 0.884) and 0.868 (95% CI, 0.784 ~ 0.929), respectively. Both deep learning models performed better than the clinical model (p < 0.05). There was no statistically significant difference between the deep learning models with or without integrating clinical factors.Conclusions: Deep learning based on high‐resolution T2‐weighted magnetic resonance images showed a good predictive performance for MSI status in rectal cancer patients. The proposed model may help to identify patients who would benefit from chemotherapy or immunotherapy and determine individualized therapeutic strategies for these patients.

Hepatocellular carcinoma (HCC) is one of the most malignant tumors and the biggest obstacle in curing HCC is its high metastasis potential. Alteration of p53 is the most frequent genetic change found in HCC. Although the biological function of p53 in tumor initiation and progression has been well characterized, whether or not p53 is implicated in metastasis of HCC is largely unknown. In this study, we analyzed the potential functions of p53 in epithelial-mesenchymal transition (EMT) and metastasis of HCC cells. Both insulin- and TGF-β1-induced changes of critical EMT markers were greatly enhanced by p53 knockdown in HCC cells. The insulin- and TGF-β1-stimulated migration of HCC cells were enhanced by p53 knockdown. Furthermore, in vivo metastasis of HCC cells using different mouse models was robustly enhanced by p53 knockdown. In addition, we found that p53 regulation on EMT and metastasis involves β-catenin signaling. The nuclear accumulation and transcriptional activity of β-catenin was modulated by p53. The enhanced EMT phenotype, cell migration and tumor metastasis of HCC cells by p53 knockdown were abrogated by inhibiting β-catenin signal pathway. In conclusion, this study reveals that p53 plays a pivotal role in EMT and metastasis of HCC cells via its regulation on β-catenin signaling.