CDKN2A was a cuproptosis-related gene in regulating chemotherapy resistance by the MAGE-A family in breast cancer: based on artificial intelligence (AI)-constructed pan-cancer risk model.

BACKGROUND: Before the discovery of cuproptosis, copper-loaded nanoparticle is a wildly applied strategy for enhancing the tumor-cell-killing effect of chemotherapy. Although copper(ii)-related researches are wide, details of cuproptosis-related bioprocess in pan-cancer are not clear yet now, especially for prognosis and drug sensitivity prediction yet now. METHODS: In this study, VOSviewer is used for the literature review, and R4.2.0 is used for data analysis. Public data are collected from TCGA and GEO, local breast cancer cohort is collected to verify the expression level of CDKN2A. RESULTS: 7036 published articles exhibited a time-dependent linear relationship (R=0.9781, p<0.0001), and breast cancer (33.4%) is the most researched topic. Cuproptosis-related-genes (CRGs)-based unsupervised clustering divides pan-cancer subgroups into four groups (CRG subgroup) with differences in prognosis and tumor immunity. 44 tumor-driver-genes (TDGs)-based prediction model of drug sensitivity and prognosis is constructed by artificial intelligence (AI). Based on TDGs and clinical features, a nomogram is (C- index: 0.7, p= 6.958e- 12) constructed to predict the prognosis of breast cancer. Importance analysis identifies CDKN2A has a pivotal role in AI modeling, whose higher expression indicates worse prognosis in breast cancer. Furthermore, inhibition of CDKN2A down-regulates decreases Snail1, Twist1, Zeb1, vimentin and MMP9, while E-cadherin is increased. Besides, inhibition of CDKN2A also decreases the expression of MEGEA4, phosphorylated STAT3, PD-L1, and caspase3, while cleaved-caspase3 is increased. Finally, we find down-regulation of CDKN2A or MAGEA inhibits cell migration and wound healing, respectively. CONCLUSIONS: AI identified CRG subgroups in pan-cancer based on CRGs-related TDGs, and 44-gene-based AI modeling is a novel tool to identify chemotherapy sensitivity in breast cancer, in which CDKN2A/MAGEA4 pathway played the most important role.

Investigation on the improvement of activated sludge dewaterability using different iron forms (ZVI vs. Fe(II))/peroxydisulfate combined vertical electro-dewatering processes.

The high moisture content (MC) of activated sludge dewatered by traditional vertical electro-dewatering (VED) is unable to meet the disposal requirements. Therefore, different iron forms (ZVI vs. Fe(II))/peroxydisulfate (PDS) combined VED (ZVI/PDS-VED and Fe(II)/PDS-VED) were employed to enhance the dewaterability of activated sludge. The dewatering behaviors of the two combined dewatering processes and the underlying mechanism related to the sludge characteristics were investigated and compared. Sludge was conditioned using ZVI/PDS and Fe(II)/PDS, respectively, and then dewatered by the VED in the experiment. Experimental results showed that with 0.3 g (g dry solids (DS))-1 of iron activators, 0.583 g (g DS) -1 of PDS, and 30 V of voltage, the MC of sludge after ZVI/PDS-VED and Fe(II)/PDS-VED reached the minimum values of 50.6 ± 1.2% and 32.1 ± 1.5%, respectively. ZVI/PDS and Fe(II)/PDS conditioning reduced the MC difference of sludge between the anode and the cathode during the VED, facilitating the water homogenization in the sludge cake. ZVI/PDS-VED and Fe(II)/PDS-VED could effectively reduce the bound water and the free water. Free water had high correlations with α-helix (r = 0.999, p < 0.05) and CO (r = 0.998, p < 0.05). Compared with the traditional VED and the ZVI/PDS-VED, the Fe(II)/PDS-VED had a greater improvement of sludge dewaterability due to the more efficient degradation of extracellular polymeric substances and the increase of sludge surface hydrophobicity. This study promoted the development of the new sludge deep-dewatering technology.