RBFOX2 confers tumor growth by PI3K/AKT and MAPK signaling in gastric cancer.

RNA-binding Fox (RBFOX)2, a member of a family of RNA-binding proteins, is well known as a regulator of alternative pre-mRNA splicing. However, its possible role in gastric cancer is unknown. In this study, we investigated the biologic role and clinical significance of RBFOX2 in gastric cancer growth and elucidated its underlying molecular mechanisms. We found that RBFOX2 was highly expressed in gastric cancer cell lines and tumor tissue compared with the adjacent nontumor tissue. We also found that RBFOX2 overexpression was correlated with poor overall survival in patients with gastric cancers. Multivariate survival analyses revealed that higher RBFOX2 expression was an independent prognostic factor for the overall survival of patients with gastric cancers. Suppression of RBFOX2 by shRNA inhibited gastric cancer cell proliferation, colony formation and induced apoptosis. Mechanism studies revealed that these effects were achieved through the simultaneous modulation of multiple signaling pathways. Knockdown of RBFOX2 expression by shRNA markedly inhibited the phosphorylation of phosphatidylinositol 3-hydroxy kinase, threonine kinase and extracellular signal-regulated kinase and Jun N-terminal kinases proteins. In contrast, the ectopic expression of RBFOX2 had the opposite effects. Moreover, RBFOX2 knockdown also induced the cleavage of caspase-3 and caspase-9 proteins. Collectively, these results demonstrate that RBFOX2 plays a critical role in regulating gastric cancer cell proliferation and survival and may be a potential prognostic biomarker and therapeutic target for gastric cancer.

SHMT2 promotes tumor growth through VEGF and MAPK signaling pathway in breast cancer.

Cancer cells modulate their metabolic activities to adapt to their growth and proliferation. Despite advances in breast cancer biology having led to the widespread use of molecular targeted therapy and hormonal drugs, the molecular mechanisms in metabolism related to the regulation of breast cancer cell proliferation are still poorly understood. Here, we investigate the possible role of SHMT2, a key enzyme in serine metabolism, in breast cancer. Firstly, SHMT2 is found highly expressed in both breast cancer cells and tissues, and patients with high expression of SHMT2 have a worse prognosis. Moreover, the intervention of SHMT2 by either knockdown or over-expression in vitro induces the effect on breast cancer proliferation. Mechanistically, RNA-seq shows that over-expression of SHMT2 affect multiple signaling pathways and biological process in breast cancer cells. Furthermore, we confirm that SHMT2 promotes breast cancer cell growth through MAPK and VEGF signaling pathways. Finally, we verify the role of SHMT2 in promoting breast cancer growth in the xenograft tumor model. Our results indicate that SHMT2 plays a critical role in regulating breast cancer growth through MAPK, and VEGF signaling pathways, and maybe serve as a therapeutic target for breast cancer therapy.

Pan-Immune-Inflammation Value: A New Prognostic Index in Operative Breast Cancer.

Background: To build a predictive scoring model based on simple immune and inflammatory parameters to predict postoperative survival in patients with breast cancer. Methods: We used a brand-new immuno-inflammatory index-pan-immune-inflammation value (PIV)-to retrospectively evaluate the relationship between PIV and overall survival (OS), and based on the results of Cox regression analysis, we established a simple scoring prediction model based on several independent prognostic parameters. The predictive accuracy of the model was evaluated and independently validated. Results: A total of 1,312 patients were included for analysis. PIV was calculated as follows: neutrophil count (109/L) × platelet count (109/L) × monocyte count (109/L)/lymphocyte count (109/L). According to the best cutoff value of PIV, we divided the patients into two different subgroups, high PIV (PIV > 310.2) and low PIV (PIV ≤ 310.2), associated with significantly different survival outcomes (3-year OS, 80.26% vs. 86.29%, respectively; 5-year OS, 62.5% vs. 71.55%, respectively). Six independent prognostic factors were identified and used to build the scoring system, which performed well with a concordance index (C-index) of 0.759 (95% CI: 0.715-0.802); the calibration plot showed good calibration. Conclusions: We have established and verified a simple scoring system for predicting prognosis, which can predict the survival of patients with operable breast cancer. This system can help clinicians implement targeted and individualized treatment strategies.

A Model Combining Skeletal Muscle Mass and a Hematological Biomarker to Predict Survival in Patients With Nasopharyngeal Carcinoma Undergoing Concurrent Chemoradiotherapy.

BACKGROUND: Using the current tumor lymph node metastasis (TNM) staging system to make treatment decisions and predict survival in patients with nasopharyngeal carcinoma (NPC) lacks sufficient accuracy. Patients at the same stage often have different survival prognoses. METHODS: In the current study 802 NPC patients who underwent concurrent radiotherapy and chemotherapy from January 2010 to December 2014 at Sun Yat-sen University Cancer Center in China were retrospectively assessed. The optimal cut-off points for skeletal muscle index (SMI) and monocyte-to-lymphocyte ratio (MLR) were determined via receiver operating characteristic curves. SMI-MLR (S-M) grade and a nomogram were developed and used as clinical indicators in NPC patients. The consistency index (C-index) and a calibration curve were used to measure the accuracy and discriminative capacity of prediction. RESULTS: The predictive performance of S-M grade was better than that of TNM staging (C-index 0.639, range 0.578-0.701 vs. 0.605, range 0.545-0.665; p = 0.037). In multivariate analysis S-M grade, T stage, and N stage were independent prognostic factors. These three factors were then combined, yielding a nomogram with a C-index of 0.71 (range 0.64-0.77), indicating good predictive capacity. CONCLUSION: We developed and validated a prognostic parameter, S-M grade, which increased prediction accuracy significantly and can be combined with TNM staging to predict survival in patients with NPC undergoing concurrent chemoradiotherapy.