Upregulated GATA3/miR205-5p Axis Inhibits MFNG Transcription and Reduces the Malignancy of Triple-Negative Breast Cancer

Targeting C21orf58 is a Novel Treatment Strategy of Hepatocellular Carcinoma by Disrupting the Formation of JAK2/C21orf58/STAT3 Complex

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide. Functionally uncharacterized genes are an attractive repository to explore candidate oncogenes. It is demonstrated that C21orf58 displays an oncogenic role in promoting cell growth, tumorigenesis and sorafenib resistance of HCC cells by abnormal activation of STAT3 signaling. Mechanistically, a novel manner to regulate STAT3 signaling that adaptor C21orf58 forms a ternary complex is reveal with N-terminal domain of STAT3 and SH2 domain of JAK2, by which C21orf58 overactivates wild-type STAT3 by facilitating its phosphorylation mediated by JAK2, and hyper-activates of constitutively mutated STAT3 due to preferred binding with C21orf58 and JAK2. Moreover, it is validated that inhibition of C21orf58 with drug alminoprofen, selected by virtual screening, could effectively repress the viability and tumorigenesis of HCC cells. Therefore, it is identified that C21orf58 functions as an oncogenic adaptor, reveal a novel regulatory mechanism of JAK2/STAT3 signaling, explain the cause of abnormal activity of activated mutants of STAT3, and explore the attractive therapeutic potential by targeting C21orf58 in HCC.

Comprehensive genomics analysis of aging related gene signature to predict the prognosis and drug resistance of colon adenocarcinoma

Background: Colon adenocarcinoma (COAD) is a heterogeneous tumor and senescence is crucial in the occurrence of cancer. This study aimed to identify senescence-based subtypes and construct a prognostic signature to predict the prognosis and guide immunotherapy or chemotherapy decisions for COAD patients. Methods: Based on the single-cell RNA sequencing (scRNA-seq) data of 13 samples from the Gene Expression Omnibus (GEO) database, we assessed cellular senescence characteristics. Transcriptome data, copy number variations (CNVs) and single nucleotide variations (SNVs) data were obtained from The Cancer Genome Atlas (TCGA) database. GSE39582 and GSE17537 were used for validation. Senescence subtypes were identified using unsupervised consensus clustering analysis, and a prognostic signature was developed using univariate Cox analysis and least absolute shrinkage and selection operator (LASSO). Response of risk groups to chemotherapy was predicted using the half-maximal inhibitory concentration (IC50) values. We further analyzed the relationship between risk gene expression and methylation level. The prediction performance was assessed by nomogram. Results: Senescence-related pathways were highly enriched in malignant cells and bulk RNA-seq verified cellular senescence. Three senescence subtypes were identified, in which patients in clust3 had poorest prognosis and higher T stage, accompanied with higher tumor mutation burden (TMB) and mutations, activated inflammatory response, more immune cell infiltration, and higher immune escape tendency. A senescence-based signature using 11 genes (MFNG, GPRC5B, TNNT1, CCL22, NOXA1, PABPC1L, PCOLCE2, MID2, CPA3, HSPA1A, and CALB1) was established, and accurately predicted a lower prognosis in high risk patients. Its robustness was validated by external cohort. Low risk patients were more sensitive to small molecule drugs including Erlotinib, Sunitinib, MG-132, CGP-082996, AZ628, Sorafenib, VX-680, and Z-LLNle-CHO. Risk score was an independent prognostic factor and nomogram confirmed its reliability. Four risk genes (CALB1, CPA3, NOXA1, and TNNT1) had significant positive correlation with their methylation level, while six genes (CCL22, GPRC5B, HSPA1A, MFNG, PABPC1L, and PCOLCE2) were negatively correlated with their methylation level. Conclusion: This study provides novel understanding of heterogeneity in COAD from the perspective of senescence, and develops signatures for prognosis prediction in COAD.