Decreased expression of CLCA2 and the correlating with immune infiltrates in patients with cervical squamous cell carcinoma: A bioinformatics analysis

Rps3 Attenuates Gastric Precancerous Lesions by Promoting Dendritic Cells Maturation via AKT/β-Catenin Pathway

This study aimed to investigate the dysregulated proteins and the underlying mechanisms of gastric precancerous lesions. Proteomic and phosphoproteomic methods were used to characterize the proteome and phosphoproteome profiles of N-methyl-N-nitro-N-nitrosoguanidine (MNNG)-induced gastric precancerous lesions. The hub differentially expressed proteins (DEPs) and phosphoproteins (DEPPs) were identified by using differential expression and protein-protein interaction network analyses. Western blot assay, quantitative reverse transcription (qRT)-PCR, and CCK-8 assays detected the expression of Rps3, N-cadherin, E-cadherin, AKT, p-AKT, and β-catenin and verified the roles of Rps3 on the MNNG-induced human gastric epithelial cell line (GES-1) cells. Hub DEPs and phosphoproteins Rps3, Akt1, and Ctnnb1 were significantly correlated with five dendritic cells (DCs) pathways, and Akt1 and Ctnnb1 were significantly negatively correlated with Rps3. MNNG administration markedly reduced the Rps3 mRNA and protein expression levels (all P < 0.05). Overexpression of Rps3 significantly inhibited tumorigenesis of MNNG-induced GES-1 cells (all P < 0.01) and changed the protein levels of N-cadherin, E-cadherin, AKT, p-AKT, and β-catenin. Similarly, SC79 treatment substantially increased the expression of interleukin (IL)-6, IL-10, and vascular endothelial growth factor (all P < 0.05). Rps3 was poorly expressed in precancerous gastric lesions. Correspondingly, overexpression of Rps3 promoted DC maturation via the AKT/β-catenin pathway, inhibiting the progression of gastric precancerous lesions.

Ion Channels and Personalized Medicine in Gynecological Cancers

Targeted therapy against cancer plays a key role in delivering safer and more efficient treatments. In the last decades, ion channels have been studied for their participation in oncogenic processes because their aberrant expression and/or function have been associated with different types of malignancies, including ovarian, cervical, and endometrial cancer. The altered expression or function of several ion channels have been associated with tumor aggressiveness, increased proliferation, migration, invasion, and metastasis of cancer cells and with poor prognosis in gynecological cancer patients. Most ion channels are integral membrane proteins easily accessible by drugs. Interestingly, a plethora of ion channel blockers have demonstrated anticancer activity. Consequently, some ion channels have been proposed as oncogenes, cancer, and prognostic biomarkers, as well as therapeutic targets in gynecological cancers. Here, we review the association of ion channels with the properties of cancer cells in these tumors, which makes them very promising candidates to be exploited in personalized medicine. The detailed analysis of the expression pattern and function of ion channels could help to improve the clinical outcomes in gynecological cancer patients.

CLCA2 overexpression suppresses epithelial-to-mesenchymal transition in cervical cancer cells through inactivation of ERK/JNK/p38-MAPK signaling pathways

Cervical cancer is an important malignant tumor threatening the physical and mental health of women in the world. As a new calcium activated chloride channel protein, calcium activated chloride channel (CLCA2) plays an important role in tumorigenesis and development. But its role and exact regulatory mechanism in cervical cancer are still unclear. In our study, we found CLCA2 was significantly decreased in cervical cancer cells, and overexpression of CLCA2 inhibited the proliferation, migration and invasion, and promotes apoptosis of cervical cancer cells, and CLCA2 inhibited EMT (Epithelial-mesenchymal transition) through an p38 / JNK / ERK pathway. The results in vivo were consistent with those in vitro. In conclusion, overexpression of CLCA2 inhibited the progression of cervical cancer in vivo and in vitro. This may provide a theoretical basis for CLCA2 as a new indicator of clinical diagnosis and prognosis of cervical cancer or as a potential target of drug therapy.

Triple-Negative Breast Cancer Analysis Based on Metabolic Gene Classification and Immunotherapy

Triple negative breast cancer (TNBC) has negative expression of ER, PR and HER-2. TNBC shows high histological grade and positive rate of lymph node metastasis, easy recurrence and distant metastasis. Molecular typing based on metabolic genes can reflect deeper characteristics of breast cancer and provide support for prognostic evaluation and individualized treatment. Metabolic subtypes of TNBC samples based on metabolic genes were determined by consensus clustering. CIBERSORT method was applied to evaluate the score distribution and differential expression of 22 immune cells in the TNBC samples. Linear discriminant analysis (LDA) established a subtype classification feature index. Kaplan-Meier (KM) and receiver operating characteristic (ROC) curves were generated to validate the performance of prognostic metabolic subtypes in different datasets. Finally, we used weighted correlation network analysis (WGCNA) to cluster the TCGA expression profile dataset and screen the co-expression modules of metabolic genes. Consensus clustering of the TCGA cohort/dataset obtained three metabolic subtypes (MC1, MC2, and MC3). The ROC analysis showed a high prognostic performance of the three clusters in different datasets. Specifically, MC1 had the optimal prognosis, MC3 had a poor prognosis, and the three metabolic subtypes had different prognosis. Consistently, the immune characteristic index established based on metabolic subtypes demonstrated that compared with the other two subtypes, MC1 had a higher IFNγ score, T cell lytic activity and lower angiogenesis score, T cell dysfunction and rejection score. TIDE analysis showed that MC1 patients were more likely to benefit from immunotherapy. MC1 patients were more sensitive to immune checkpoint inhibitors and traditional chemotherapy drugs Cisplatin, Paclitaxel, Embelin, and Sorafenib. Multiclass AUC based on RNASeq and GSE datasets were 0.85 and 0.85, respectively. Finally, based on co-expression network analysis, we screened 7 potential gene markers related to metabolic characteristic index, of which CLCA2, REEP6, SPDEF, and CRAT can be used to indicate breast cancer prognosis. Molecular classification related to TNBC metabolism was of great significance for comprehensive understanding of the molecular pathological characteristics of TNBC, contributing to the exploration of reliable markers for early diagnosis of TNBC and predicting metastasis and recurrence, improvement of the TNBC staging system, guiding individualized treatment.