High expression of CIN85 promotes proliferation and invasion of human esophageal squamous cell carcinoma

PIK3R1 fusion drives chemoresistance in ovarian cancer by activating ERK1/2 and inducing rod and ring-like structures

Gene fusions are common in high-grade serous ovarian cancer (HGSC). Such genetic lesions may promote tumorigenesis, but the pathogenic mechanisms are currently poorly understood. Here, we investigated the role of a PIK3R1-CCDC178 fusion identified from a patient with advanced HGSC. We show that the fusion induces HGSC cell migration by regulating ERK1/2 and increases resistance to platinum treatment. Platinum resistance was associated with rod and ring-like cellular structure formation. These structures contained, in addition to the fusion protein, CIN85, a key regulator of PI3K-AKT-mTOR signaling. Our data suggest that the fusion-driven structure formation induces a previously unrecognized cell survival and resistance mechanism, which depends on ERK1/2-activation.

Actin-like protein 8, a member of cancer/testis antigens, supports the aggressive development of oral squamous cell carcinoma cells via activating cell cycle signaling

Due to the malignancy of oral squamous cell carcinoma (OSCC), investigations of novel therapeutic targets and prognostic biomarkers are urgently needed. In our present study, significant up-regulation of Actin-like protein 8 (ACTL8) in OSCC patients was observed by bioinformatics analysis with RNA sequencing data obtained from The Cancer Genome Atlas (TCGA) database. The results of Chi-square test revealed that there was a significant correlation between ACTL8 expression and tumor status (T1 + T2/T3+T4) (P = 0.004). Survival analysis indicated a negative correlation between ACTL8 overexpression and prognosis in OSCC (P = 3.984e-02). An ACTL8 knockdown experiment was conducted to evaluate the function of ACTL8 on OSCC cell biological behaviors. The results revealed that knockdown of ACTL8 significantly inhibited the growth and mobility, arrested cell cycle and promoted apoptosis of TCA-83 and CAL27 cells. Moreover, Gene Set Enrichment Analysis (GSEA) and western blots demonstrated that activation of cell cycle signaling pathway was inhibited by knockdown of ACTL8, as we observed the down-regulation of 4 key proteins (CDK1, cyclin E1, cyclin B2 and c-Myc) in this pathway. The present investigation indicates that ACTL8 plays an oncogenic role in the pathogenesis of OSCC, suggesting that ACTL8 may be a promising therapeutic target and prognosis marker for human OSCC.

Identification of Immune-Cell-Related Prognostic Biomarkers of Esophageal Squamous Cell Carcinoma Based on Tumor Microenvironment

Background

Esophageal squamous cell carcinoma (ESCC) is one of the most fatal cancers in the world. The 5-year survival rate of ESCC is <30%. However, few biomarkers can accurately predict the prognosis of patients with ESCC. We aimed to identify potential survival-associated biomarkers for ESCC to improve its poor prognosis.

Methods

ImmuneAI analysis was first used to access the immune cell abundance of ESCC. Then, ESTIMATE analysis was performed to explore the tumor microenvironment (TME), and differential analysis was used for the selection of immune-related differentially expressed genes (DEGs). Weighted gene coexpression network analysis (WGCNA) was used for selecting the candidate DEGs. Least absolute shrinkage and selection operator (LASSO) Cox regression was used to build the immune-cell-associated prognostic model (ICPM). Kaplan–Meier curve of survival analysis was performed to evaluate the efficacy of the ICPM.

Results

Based on the ESTIMATE and ImmuneAI analysis, we obtained 24 immune cells’ abundance. Next, we identified six coexpression module that was associated with the abundance. Then, LASSO regression models were constructed by selecting the genes in the module that is most relevant to immune cells. Two test dataset was used to testify the model, and we finally, obtained a seven-genes survival model that performed an excellent prognostic efficacy.

Conclusion

In the current study, we filtered seven key genes that may be potential prognostic biomarkers of ESCC, and they may be used as new factors to improve the prognosis of cancer.