RACGAP1 knockdown synergizes and enhances the effects of chemotherapeutics on ovarian cancer.

Among the three most prevalent cancers affecting the female reproductive system, ovarian cancer (OV) ranks as the second most frequently diagnosed. It is important to investigate the genomic complexity of OV to develop diagnostic and therapeutic strategies. Through the utilization of bioinformatics analysis, it was determined that RacGTPase Activating Protein 1 (RACGAP1) holds significant significance in the field of OV chemotherapeutics, an aspect that has not been thoroughly explored in prior investigations. In our study, a notable increase in RACGAP1 expression was detected in ovarian cancer, demonstrating a robust association with clinicopathological features and patient prognosis. In vivo and in vitro testing revealed that RACGAP1 acts synergistically with chemotherapeutics to enhance their effects on ovarian cancer. Furthermore, an interaction between RACGAP1 and the subunit G2 of the condensin II complex, known as non-SMC condensin II complex subunit G2 (NCAPG2), has been identified. Our findings may provide new insight for improving therapeutic strategies for OV.

MAOA suppresses the growth of gastric cancer by interacting with NDRG1 and regulating the Warburg effect through the PI3K/AKT/mTOR pathway.

OBJECTIVE: Previous studies have indicated that neurotransmitters play important roles in the occurrence and development of gastric cancer. MAOA is an important catecholamine neurotransmitter-degrading enzyme involved in the degradation of norepinephrine, epinephrine and serotonin. To find a potential therapeutic target for the treatment of gastric cancer, the biological functions of MAOA and the underlying mechanism in gastric cancer need to be explored. METHODS: The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) datasets, Kaplan‒Meier (KM) plotter were used to identify the differentially expressed genes, which mainly involved the degradation and synthesis enzymes of neurotransmitters in gastric cancer. We also investigated the expression pattern of MAOA in human and mouse tissues and cell lines by immunohistochemistry and Western blotting analysis. Western blotting, quantitative real-time PCR, enzyme-linked immunosorbent assay (ELISA) and a Seahorse experiment were used to identify the molecular mechanism of cancer cell glycolysis. MAOA expression and patient survival were analysed in the Ren Ji cohort, and univariate and multivariate analyses were performed based on the clinicopathological characteristics of the above samples. RESULTS: MAOA expression was significantly downregulated in gastric cancer tissue and associated with poor patient prognosis. Moreover, the expression level of MAOA in gastric cancer tissue had a close negative correlation with the SUXmax value of PET-CT in patients. MAOA suppressed tumour growth and glycolysis and promoted cancer cell apoptosis. We also reported that MAOA can interact with NDRG1 and regulate glycolysis through suppression of the PI3K/Akt/mTOR pathway. MAOA expression may serve as an independent prognostic factor in gastric cancer patients. CONCLUSIONS: MAOA attenuated glycolysis and inhibited the progression of gastric cancer through the PI3K/Akt/mTOR pathway. Loss of function or downregulation of MAOA can facilitate gastric cancer progression. Overexpression of MAOA and inhibition of the PI3K/Akt/mTOR pathway may provide a potential method for gastric cancer treatment in clinical therapeutic regimens.

The SLITRK4-CNPY3 axis promotes liver metastasis of gastric cancer by enhancing the endocytosis and recycling of TrkB in tumour cells.

PURPOSE: Gastric cancer (GC) is a malignant tumour with high mortality, and liver metastasis is one of the main causes of poor prognosis. SLIT- and NTRK-like family member 4 (SLITRK4) plays an important role in the nervous system, such as synapse formation. Our study aimed to explore the functional role of SLITRK4 in GC and liver metastasis. METHODS: The mRNA level of SLITRK4 was evaluated using publicly available transcriptome GEO datasets and Renji cohort. The protein level of SLITRK4 in the tissue microarray of GC was observed using immunohistochemistry. Cell Counting Kit-8, colony formation, transwell migration assays in vitro and mouse model of liver metastasis in vivo was performed to investigate the functional roles of SLITRK4 in GC. Bioinformatics predictions and Co-IP experiments were applied to screen and identify SLITRK4-binding proteins. Western blot was performed to detect Tyrosine Kinase receptor B (TrkB)-related signaling molecules. RESULTS: By comparing primary and liver metastases from GC, SLITRK4 was found to be upregulated in tissues of GC with liver metastasis and to be closely related to poor clinical prognosis. SLITRK4 knockdown significantly abrogated the growth, invasion, and metastasis of GC in vitro and in vivo. Further study revealed that SLITRK4 could interact with Canopy FGF Signalling Regulator 3 (CNPY3), thus enhancing TrkB- related signaling by promoting the endocytosis and recycling of the TrkB receptor. CONCLUSION: In conclusion, the CNPY3-SLITRK4 axis contributes to liver metastasis of GC according to the TrkB-related signaling pathway. which may be a therapeutic target for the treatment of GC with liver metastasis.

Spatiotemporal quantification of metastatic tumour cell growth and distribution in lymph nodes by whole-mount tissue 3D imaging.

Lymph nodes (LNs) are a common site of metastasis in many solid cancers. Tumour cells can migrate to LNs for further metastatic colonization of distant organs, indicating poor prognosis and requiring different clinical interventions. The histopathological diagnostic methods currently used to detect clinical lymph node metastasis (LNM) have limitations, such as incomplete visualization. To obtain a complete picture of metastatic LNs on the spatial and temporal scales, we used ultimate 3D imaging of solvent-cleared organs (uDISCO) and 3D rapid immunostaining. MC38 cells labelled with EGFP were injected into the left footpads of C57BL/6 mice. Draining lymph nodes (DLNs) harvested from these mice were cleared using the uDISCO method. Metastatic colorectal cancer (CRC) cells in various regions of DLNs from mice at different time points were quantified using 3D imaging of whole-mount tissue. Several stages of tumour cell growth and distribution in LNs were identified: 1) invasion of lymphatic vessels (LVs) and blood vessels (BVs); 2) dispersion outside LVs and BVs for proliferation and expansion; and 3) re-entry into BVs and efferent lymphatic vessels (ELVs) for further distant metastasis. Moreover, these data demonstrated that mouse fibroblast cells (MFCs) could not only promote LNM of tumour cells but also metastasize to LNs together with tumour cells, thus providing a "soil" for tumour cell colonization. In conclusion, 3D imaging of whole-mount tissue and spatiotemporal analysis of LNM may collectively constitute an auxiliary method to improve the accuracy of clinical LNM detection.