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Death receptor-mediated extrinsic apoptosis system had been developed as a promising therapeutic strategy in clinical oncology, such as TRAIL therapy. However, multiple studies have demonstrated that TRAIL resistance is the biggest problem for disappointing clinical trials despite preclinical success. Targeting cellular FLICE inhibitory protein (cFLIP) is one strategy of combinatorial therapies to overcome resistance to DR-mediated apoptosis due to its negative regulator of extrinsic apoptosis. E × 527 (Selisistat) is a specific inhibitor of SIRT1 activity with safe and well tolerance in clinical trials. Here, we show that E × 527 could strengthen significantly activation of rhFasL-mediated apoptotic signaling pathway and increased apoptotic rate of T leukemia cells with high expression of cFLIP. Mechanically, Inhibition of SIRT1 by E × 527 increased polyubiquitination level of cFLIP via increasing acetylation of Ku70, which could promote proteosomal degradation of cFLIP protein. It implied that combinatorial therapies of E × 527 plus TRAIL may have a potential as a novel clinical application for TRAIL-resistant hematologic malignancies.

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The SCG5 gene has been demonstrated to play an essential role in the development and progression of a range of malignant neoplasms. The regulation of SCG5 expression involves multiple biological pathways. According to relevant studies, SCG5 is differentially expressed in different cancers, and its up- or down-regulation may even affect tumour growth, invasion, and migration, which caught our attention. Therefore, we summarise the regulatory roles played by the SCG5 gene in a variety of cancers and the biological regulatory mechanisms associated with its possible promotion or inhibition of tumour biological behavior, to further explore the potential of SCG5 as a new tumour marker and hopefully provide theoretical guidance for subsequent disease research and treatment.

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Luteolin (3, 4, 5, 7-tetrahydroxyflavone) are natural flavonoids widely found in vegetables, fruits and herbs, with anti-tumor, anti-inflammatory and antioxidant effects, and also play an anti-cancer effect in various cancers such as lung, breast, prostate, and liver cancer, etc. Specifically, the anti-cancer mechanism includes regulation of various signaling pathways to induce apoptosis of tumor cells, inhibition of tumor cell proliferation and metastasis, anti-angiogenesis, regulation of immune function, synergistic anti-cancer drugs and regulation of reactive oxygen species levels of tumor cells. Specific anti-cancer mechanisms include regulation of various signaling pathways to induce apoptosis, inhibition of tumor cell proliferation and metastasis, anti-angiogenesis, reversal of epithelial-mesenchymal transition, regulation of immune function, synergism with anti-cancer drugs and regulation of reactive oxygen species levels in tumor cells. This paper integrates the latest cutting-edge research on luteolin and combines it with the prospect of future clinical applications, aiming to explore the mechanism of luteolin exerting different anticancer effects through the regulation of different signaling pathways, so as to provide a practical theoretical basis for the use of luteolin in clinical treatment and hopefully provide some reference for the future research direction of luteolin.

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BACKGROUND: Accurate preoperative prediction of lymph node metastasis (LNM) in esophageal cancer (EC) patients is of crucial clinical significance for treatment planning and prognosis. AIM: To develop a clinical radiomics nomogram that can predict the preoperative lymph node (LN) status in EC patients. METHODS: A total of 32 EC patients confirmed by clinical pathology (who underwent surgical treatment) were included. Real-time fluorescent quantitative reverse transcription-polymerase chain reaction was used to detect the expression of B7-H3 mRNA in EC tissue obtained during preoperative gastroscopy, and its correlation with LNM was analyzed. Radiomics features were extracted from multi-modal magnetic resonance imaging of EC using Pyradiomics in Python. Feature extraction, data dimensionality reduction, and feature selection were performed using XGBoost model and leave-one-out cross-validation. Multivariable logistic regression analysis was used to establish the prediction model, which included radiomics features, LN status from computed tomography (CT) reports, and B7-H3 mRNA expression, represented by a radiomics nomogram. Receiver operating characteristic area under the curve (AUC) and decision curve analysis (DCA) were used to evaluate the predictive performance and clinical application value of the model. RESULTS: The relative expression of B7-H3 mRNA in EC patients with LNM was higher than in those without metastasis, and the difference was statistically significant (P < 0.05). The AUC value in the receiver operating characteristic (ROC) curve was 0.718 (95%CI: 0.528-0.907), with a sensitivity of 0.733 and specificity of 0.706, indicating good diagnostic performance. The individualized clinical prediction nomogram included radiomics features, LN status from CT reports, and B7-H3 mRNA expression. The ROC curve demonstrated good diagnostic value, with an AUC value of 0.765 (95%CI: 0.598-0.931), sensitivity of 0.800, and specificity of 0.706. DCA indicated the practical value of the radiomics nomogram in clinical practice. CONCLUSION: This study developed a radiomics nomogram that includes radiomics features, LN status from CT reports, and B7-H3 mRNA expression, enabling convenient preoperative individualized prediction of LNM in EC patients.

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Both the epidermal growth factor receptor (EGFR) and insulin-like growth factor 1 receptor (IGF-1R) have been implicated in the development of cancers, and the increased expression of both receptors has been observed in esophageal cancer. However, the tyrosine kinase inhibitors of both receptors have thus far failed to provide clinical benefits for esophageal cancer patients. Studies have confirmed the complicated crosstalks that exist between the EGFR and IGF-1R pathways. The EGFR and IGF-1R signals act as mutual compensation pathways, thereby conveying resistance to EGFR or IGF-1R inhibitors when used alone. This study evaluated the antitumor efficacy of the EGFR/HER2 inhibitors, gefitinib and lapatinib, in combination with the IGF-1R inhibitor, linsitinib, on the esophageal squamous cell carcinoma (ESCC). Gefitinib or lapatinib, in combination with linsitinib, synergistically inhibited the proliferation, migration, and invasion of ESCC cells, caused significant cell cycle arrest, and induced marked cell apoptosis. Their combination demonstrated stronger inhibition on the activation of EGFR, HER2, and IGF-1R as well as the downstream signaling molecules. In vivo, the addition of linsitinib to gefitinib or lapatinib also potentiated the inhibition effects on the growth of xenografts. Our results suggest the next clinical exploration of the combination of gefitinib or lapatinib with linsitinib in the treatment of ESCC patients.

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KEY MESSAGE: We developed the ZDX1 high-throughput functional soybean array for high accuracy evaluation and selection of both parents and progeny, which can greatly accelerate soybean breeding. Microarray technology facilitates rapid, accurate, and economical genotyping. Here, using resequencing data from 2214 representative soybean accessions, we developed the high-throughput functional array ZDX1, containing 158,959 SNPs, covering 90.92% of soybean genes and sites related to important traits. By application of the array, a total of 817 accessions were genotyped, including three subpopulations of candidate parental lines, parental lines and their progeny from practical breeding. The fixed SNPs were identified in progeny, indicating artificial selection during the breeding process. By identifying functional sites of target traits, novel soybean cyst nematode-resistant progeny and maturity-related novel sources were identified by allele combinations, demonstrating that functional sites provide an efficient method for the rapid screening of desirable traits or gene sources. Notably, we found that the breeding index (BI) was a good indicator for progeny selection. Superior progeny were derived from the combination of distantly related parents, with at least one parent having a higher BI. Furthermore, new combinations based on good performance were proposed for further breeding after excluding redundant and closely related parents. Genomic best linear unbiased prediction (GBLUP) analysis was the best analysis method and achieved the highest accuracy in predicting four traits when comparing SNPs in genic regions rather than whole genomic or intergenic SNPs. The prediction accuracy was improved by 32.1% by using progeny to expand the training population. Collectively, a versatile assay demonstrated that the functional ZDX1 array provided efficient information for the design and optimization of a breeding pipeline for accelerated soybean breeding.

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