Background: Triple-negative breast cancer has become an intricate part and hotspot in the clinical and experimental research. Connexins, serving as functional proteins in gap junctions, play an important role in tumorigenesis, cell proliferation and metastasis. Methods: We constructed and employed the Connexin 43 (Cx43) overexpression lentiviral vectors and Cx43 siRNA in paclitaxel-treated MDA-MB-231 cells. We performed the experiments of clonal formation and flow cytometry to gauge the effect of paclitaxel on cellular behaviors and immunofluorescence and subsequent quantitative RT-PCR and Western blot to examine the expression of genes and corresponding proteins. Experiments of scrape loading/dye transfer were utilized to explore the gap junctions. The targets of Cx43 were identified via the experiments of co-immunoprecipitation (Co-IP), GST pull-down assays and proximal ligation assay (PLA). Results: The results showed that Cx43 hindered cell proliferation and promoted apoptosis in the paclitaxel-treated MDA-MB-231 cells. Overexpressed Cx43 suppressed the expression of resistance genes such as BRCP, Txr-1, α-tubulin and β-tubulin and promoted the expression of apoptosis gene as TSP-1 and Bcl-2. Cx43 was also positively related to ITGα9 and negatively related to ITGαV and ITGα11. The gap junctions altered magnificently under different expressions of Cx43, which indicated that Cx43 could promote the number of intercellular gap junctions. The immunofluorescent experiment revealed that both of Cx43 and β-tubulin were mainly localized in the cytoplasm. The assays of Co-IP and GST pull-down demonstrated that there existed a direct interaction between Cx43 and β-tubulin. Furthermore, the result of PLA also showed that Cx43 interacts with β-tubulin in MDA-MB-231 cells. Conclusion: Overexpression of Cx43 could modulate the cellular resistance to paclitaxel via targeting β-tubulin in triple-negative breast cancer.
Background: Breast cancer is the most common malignancy in women worldwide, but few genes have been reported to be involved in breast cancer development. Methods: We constructed a co-expression network to expand upon the knowledge of the various molecular biomarkers in breast cancer development. Transcriptome data for the tissues of all breast cancer and para-carcinoma types were retrieved from The Cancer Genome Atlas (TCGA) database. We performed a co-expression analysis of breast cancer transcriptome data using Pearson’s correlation coefficient (PCC) for inter-sequence mutual rank (MR)-based cutoffs using 11 guide genes and employed Kaplan-Meier survival analyses to assess the prognostic values of hub genes. Results: A co-expression network centered on the Integrin α 11 (ITGA11) of the extracellular matrix (including 11 guide genes and 72 edge genes) was extracted for breast cancer. The gene ontology (GO) analysis showed that various genes may also be included in the breast cancer network. Among them, CEMIP, COL11A1, CTHRC1, ITGA11, LUM and P4HA3 were negatively associated with the overall survival, and ADAMTS12 and LOXL1 were positively associated with the overall survival at early stage. However, there was no significant difference between the eight gene expressions and Disease-free survival. Conclusions: Our co-expression analysis includes the isolated transcriptome of breast cancer, which is a useful resource for breast cancer researchers, as it enables them to elucidate important and complex biological events to prevent and predict cancer.
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