Introduction: A disintegrin and metallopeptidase with thrombospondin motifs (ADAMTSs), whose expression is dysregulated in various cancers, is implicated in cancer development. Herein, we aimed to investigate the functional role of ADAMTS8 in breast cancer (BC) and explore the underlying mechanisms. Methods: The protein expression of ADAMTS8 in BC cell lines and tumor tissues from BC patients was quantified by Western blot. ADAMTS8 overexpression was induced by transfection with pEZ-M90-ADAMTS8 plasmid using lipofectamine 2000. To generate ADAMTS8 stable knockdown cells, MDA-MB-231 cells were transfected with psi-H1-ADAMTS8siRNA plasmids. Cell counting kit-8 (CCK-8) assay, wound-healing assay, transwell assay and flow cytometry assay were employed to analyze the effects of ADAMTS8 on the proliferation, migration, invasion and apoptosis of BC cells. Chemosensitivity also was assessed using CCK-8 assay. The expressions of β-catenin, MMP-7 and c-Myc were measured by Western blot. Results: Our results showed that ADAMTS8 expression was significantly lower in BC tissues than that in adjacent non-tumor tissues. Overexpression of ADAMTS8 in MDA-MB-453 cells could inhibit the cell proliferation, migration and invasion and promote apoptosis. ADAMTS8 knockdown displayed the reverse effect in MDA-MB-231 cells. Consistently, in vivo data showed that ADAMTS8 overexpression led to a reduction in tumor growth. In addition, chemosensitivity testing in MDA-MB-453 cells transfected with pEZ-M90-ADAMTS8 plasmid indicated that cisplatin inhibited cell growth dramatically. Furthermore, attenuated β-catenin, MMP-7 and c-Myc level was detected after ADAMTS8 overexpression. Conclusion: These results indicate that increased ADAMTS8 expression could modify the progression of BC by inhibiting cell proliferation and invasion while promoting the apoptosis of BC cells. Thus, ADAMTS8 represents a potential therapeutic target for BC therapy.
ObjectivesTo develop and validate magnetic resonance imaging (MRI)-based pre-Radiomics and delta-Radiomics models for predicting the treatment response of local advanced rectal cancer (LARC) to neoadjuvant chemoradiotherapy (NCRT).MethodsBetween October 2017 and August 2022, 105 LARC NCRT-naïve patients were enrolled in this study. After careful evaluation, data for 84 patients that met the inclusion criteria were used to develop and validate the NCRT response models. All patients received NCRT, and the post-treatment response was evaluated by pathological assessment. We manual segmented the volume of tumors and 105 radiomics features were extracted from three-dimensional MRIs. Then, the eXtreme Gradient Boosting algorithm was implemented for evaluating and incorporating important tumor features. The predictive performance of MRI sequences and Synthetic Minority Oversampling Technique (SMOTE) for NCRT response were compared. Finally, the optimal pre-Radiomics and delta-Radiomics models were established respectively. The predictive performance of the radionics model was confirmed using 5-fold cross-validation, 10-fold cross-validation, leave-one-out validation, and independent validation. The predictive accuracy of the model was based on the area under the receiver operator characteristic (ROC) curve (AUC).ResultsThere was no significant difference in clinical factors between patients with good and poor reactions. Integrating different MRI modes and the SMOTE method improved the performance of the radiomics model. The pre-Radiomics model (train AUC: 0.93 ± 0.06; test AUC: 0.79) and delta-Radiomcis model (train AUC: 0.96 ± 0.03; test AUC: 0.83) all have high NCRT response prediction performance by LARC. Overall, the delta-Radiomics model was superior to the pre-Radiomics model.ConclusionMRI-based pre-Radiomics model and delta-Radiomics model all have good potential to predict the post-treatment response of LARC to NCRT. Delta-Radiomics analysis has a huge potential for clinical application in facilitating the provision of personalized therapy.
Background The glycolytic enzyme, α-Enolase (ENO1), catalyzes the production of phosphoenolpyruvate from 2-phosphoglycerate, thereby enhancing glycolysis and contributing to tumor progression. In the present study, we aimed to determine the role of ENO1 in skin cutaneous melanoma (SKCM) and the potential underlying mechanism. Methods The Sangerbox database was used to analyze the mRNA expression of ENO1 in SKCM. Western blotting was used to assess the levels of ENO1, c-Myc, β-catenin, MMP-9, PGAM1, and MMP-13 in SKCM-derived cell lines or tumor tissues from patients with SKCM. The pCMV-SPORT6-ENO1 and pET-28a-ENO1siRNA plasmids were used to overexpress and knockdown ENO1 in SKCM cells, respectively. To determine the function of ENO1 in the malignant behavior of SKCM cells, we performed a wound-healing assay, cell counting kit 8 assay, and transwell chamber analyses. The production of pyruvate and lactic acid in tumor cells was evaluated using their respective kits. Results Compared with non-tumor tissues, ENO1 was found to be overexpressed in SKCM tissues. In SKCM cells, ENO1 overexpression promoted invasion, migration, and proliferation of tumor cells; increased pyruvate and lactate production; and increased β-catenin, MMP-9, MMP-13, and c-Myc levels. The opposite effects were observed in SKCM cells silenced for ENO1. Conclusions These results indicate that ENO1 is involved in SKCM progression by enhancing the invasion and proliferation of tumor cells. In addition, ENO1 might have an important function in tumor cell glycolysis. Therefore, ENO1 represents a potential therapeutic target for treatment of SKCM.
Introduction The glycolytic enzyme, α-Enolase (ENO1), catalyzes the production of phosphoenolpyruvate from 2-phosphoglycerate, which enhances glycolysis, and thus contributes to tumor progression. In the present study, we aimed to determine ENO1’s role in malignant melanoma (MM) and the potential underlying mechanism. Methods Western blotting was used to assess the levels of ENO1, c-Myc, β-catenin, MMP-9, PGAM1, and MMP-13 in MM-derived cell lines or tumor tissues from patients with MM. Plasmids pCMV-SPORT6-ENO1 and pET-28a-ENO1siRNA plasmids were used to overexpress and knockdown ENO1 in MM cells, respectively. To determine the function of ENO1 in the malignant behavior of MM cells, we performed wound healing, Cell counting kit 8, Transwell chamber, and flow cytometry analyses. Pyruvate determination and lactic acid kits were used to evaluate the production of pyruvate and lactic acid in tumor cells. Results The protein levels of ENO1 and PGAM1 in MM tissue were significantly higher than that in mole tissue. In MM cells, ENO1 overexpression inhibited apoptosis; promoted invasion, migration, and proliferation; increased pyruvate and lactate production; and increased in β-catenin, MMP-9, MMP-13, and c-Myc levels. The opposite effects were observed in MM cells silenced for ENO1. Conclusion These results indicated that ENO1 is involved in MM progression by enhancing invasion and proliferation, while inhibiting apoptosis. In addition, ENO1 might have an important function in tumor cell glycolysis. Therefore, ENO1 represents a potential therapeutic target to treat MM.
Autophagy plays a dual role in tumor development and autophagy-related genes (ARGs) involved in the development of cancer. However, the correlation between these high and low risk ARGs is still unclear. To systematically study the relationship between ARGs and melanoma patients, the expression profiles of ARGs were integratedly analyzed based on the TCGA and GTEx dataset. The results suggested 8-ARGs marker can predict the prognosis of skin cutaneous melanoma (SKCM), 5-ARGs (CFLAR, DAPK2, ITGA6, DNAJB9 and RGS19) were low risk index, 3-ARGs (EIF2AK2, EGFR and PTK6) were high risk index. Further validation showed CFLAR, DNAJB9 and PTK6 were significant related to SKCM. In tumor immunization, CFLAR and DNAJB9 have stronger correlation with tumor immune cells, and there is a significant positive correlation among the low risk genes. However, there is no significant correlation between the high and low risk factors. In addition, our results also showed that CFLAR and PTK6 were significantly negatively correlated with tumor purity; PTK6 was significantly positively correlated with patient's age, CFLAR was significantly negatively correlated with patient's age; CFLAR and DNAJB9 were significantly positively correlated in purity and age. It provides a new prognostic indicator for patients and a new idea for the mechanism of autophagy in melanoma.
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