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Background: Conventional methods for predicting treatment response to neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC) are limited. Methods: This study retrospectively recruited 134 LARC patients who underwent standard nCRT followed by total mesorectal excision surgery in our institution. Based on pre-operative axial T2-weighted images, machine learning radiomics was performed. A receiver operating characteristic (ROC) curve was performed to test the efficiencies of the predictive model. Results: Among the 134 patients, 32 (23.9%) achieved pathological complete response (pCR), 69 (51.5%) achieved a good response, and 91 (67.9%) achieved down-staging. For prediction of pCR, good-response, and down-staging, the predictive model demonstrated high classification efficiencies, with an AUC value of 0.91 (95% CI: 0.83–0.98), 0.90 (95% CI: 0.83–0.97), and 0.93 (95% CI: 0.87–0.98), respectively. Conclusion: Our machine learning radiomics model showed promise for predicting response to nCRT in patients with LARC. Our predictive model based on the commonly used T2-weighted images on pelvic Magnetic Resonance Imaging (MRI) scans has the potential to be adapted in clinical practice. Novelty and Impact Statements: Methods for predicting the response of the locally advanced rectal cancer (LARC, T3-4, or N+) to neoadjuvant chemoradiotherapy (nCRT) is lacking. In the present study, we developed a new machine learning radiomics method based on T2-weighted images. As a non-invasive tool, this method facilitates prediction performance effectively. It achieves a satisfactory overall diagnostic accuracy for predicting of pCR, good response, and down-staging show an AUC of 0.908, 0.902, and 0.930 in LARC patients, respectively.

Chemotherapy resistance is one of the most common causes of death among patients with ovarian cancer, and identifying novel antitumor agents is a priority. Here, we report that the novel molecule 2‐(anaphthoyl)ethyl‐trimethylammonium iodide (α‐NETA) induces epithelial ovarian cancer (EOC) cell pyroptosis through the gesdermin‐d (GSDMD)/caspase‐4 pathway. Furthermore, Cell Counting Kit‐8 fluorescence‐activated cell sorting analysis showed that α‐NETA treatment led to cell death in different ovarian cancer cell lines, including Ho8910, Ho8910PM, and A2780. Morphologic examination by electron microscopy indicated that cells treated with α‐NETA produced multiple microbubbles, typical of cells undergoing pyroptosis. α‐NETA also significantly increased expression of pyroptosis‐associated molecules including caspase‐4 and GSDMD in EOC cells. Knockdown of either caspase‐4 or GSDMD in ovarian cancer cells strongly interfered with α‐NETA cell‐killing activity, indicating that α‐NETA acts through the pyroptosis pathway. In vivo, α‐NETA treatment dramatically decreased the size of EOC tumors in mice. Our findings suggest that α‐NETA represents a potential new antitumor molecule or lead compound for EOC chemotherapy.—Qiao, L., Wu, X., Zhang, J., Liu, L., Sui, X., Zhang, R., Liu, W., Shen, F., Sun, Y., Xi, X. α‐NETA induces pyroptosis of epithelial ovarian cancer cells through the GSDMD/caspase‐4 pathway. FASEB J. 33, 12760–12767 (2019). http://www.fasebj.org

Previous studies reported that Follistatin-like 3 (FSTL3) is abundantly expressed in several solid tumors and participate in the regulation of cell metabolism. However, the clinico-pathological significance, biological role and molecular mechanism of FSTL3 in colorectal cancer (CRC) is still unclear. Here we report that the expression level of FSTL3 in colon cancer specimens was significantly higher, compared to normal tissue and interestingly, the expression of FSTL3 was related to lymph node metastasis, tumor stage, tumor size, and intravascular emboli (IVE). As an upstream molecular event, we found that transcriptional regulation of FSTL3 was highly dependent on YAP1 de-phosphorylation events and that increased FSTL3 expression readily activated the β-Catenin pathway, which is a well-known signaling hub that promotes EMT processes and aerobic glycolysis in cancer cells. We found that elevated FSTL3 expression strongly promotes migration, invasion and metastatic formation of CRC cells by directly activating β-Catenin -mediated EMT and aerobic glycolysis. In the xenograft mouse model, FSTL3 expression was linked to increased metastatic formation of CRC cells. Together, the activation of YAP1 induces FSTL3 expression. FSTL3-mediated β-Catenin pathway activation promotes EMT and aerobic glycolysis and therefore affecting the invasive and metastatic capacity of CRC cells. The abundant FSTL3 expression is a poor prognostic factor and pharmacological targeting of YAP1 can counteract FSTL3 expression, suggesting a promising therapeutic target for anti-metastatic strategies in patients suffering from CRC.