Objective To explore a CT-based radiomics model for preoperative prediction of event-free survival (EFS) in patients with hepatoblastoma and to compare its performance with that of a clinicopathologic model. Patients and Methods Eighty-eight patients with histologically confirmed hepatoblastoma (mean age 2.28 ± 2.72 years) were recruited from two institutions between 2002 and 2019 for this retrospective study. They were divided into a training cohort (65 patients from institution A) and a validation cohort (23 patients from institution B). Radiomics features were extracted manually from pretreatment CT images in the portal venous (PV) phase. The least absolute shrinkage and selection operator (LASSO) Cox regression model was applied to construct a “radiomics signature” and radiomics score (Rad-score) for EFS prediction. Then, a nomogram incorporating the Rad-score, updated staging system, and significant variables of clinicopathologic risk (age, alpha-fetoprotein (AFP) level, histology subtype, tumor diameterthat using the clinicopathologic model. The combined model (radiomics signature plus clinicopathologic parameters) showed significant improvement in the discriminatory accuracy, along with good calibration and greater net clinical benefit, of EFS (C-Index 0.88; 95% CI 0.829-0.933). Conclusion The radiomics signature can be used as a prognostic indicator for EFS in patients with hepatoblastoma. A combination of the radiomics signature and clinicopathologic risk factors showed better performance in terms of EFS prediction in patients with hepatoblastoma, which enabled precise clinical decision-making.

Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer. At present, most patients with LUAD are diagnosed at an advanced stage, and the prognosis of advanced LUAD is poor. Hence, we aimed to identify novel biomarkers for the diagnosis and treatment of early stage LUAD and to explore their predictive value.

The microarray datasets GSE63459, GSE27262, and GSE33532 were searched, and the differentially expressed genes (DEGs) were obtained using GEO2R. The DEGs were subjected to gene ontology (GO) and pathway enrichment analyses using METASCAPE. A protein-protein interaction (PPI) network was plotted with STRING and visualized by Cytoscape. Module analysis of the PPI network was performed using MCODE. Overall survival (OS) analysis and analysis of the mRNA expression levels of genes identified by MCODE were performed with UALCAN. Western blot analysis of hub genes in LUAD patients, MTS assays, and clonogenic assays were performed to test the effects of the hub genes on cell proliferation

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A total of 341 DEGs were obtained, which were mainly enriched in terms related to blood vessel development, growth factor binding, and extracellular matrix organization. A PPI network consisting of 300 nodes and 1140 edges was constructed, and a significant module including 15 genes was identified. Elevated expression of ASPM, CCNB2, CDCA5, PRC1, KIAA0101, and UBE2T was associated with poor OS in LUAD patients. In the protein level, the hub gene was overexpressed in LUAD patients.

experiments showed that knockdown of the hub genes in the LUAD cell lines could promote cell proliferation.

DEGs are potential biomarkers for early stage lung adenocarcinoma and could have utility for the diagnosis and predicting treatment efficacy.

DEGs are potential biomarkers for early stage lung adenocarcinoma and could have utility for the diagnosis and predicting treatment efficacy.Epithelial-to-mesenchymal transition (EMT), a complicated program through which polarized epithelial cells acquire motile mesothelial traits, is regulated by tumor microenvironment. EMT is involved in tumor progression, invasion and metastasis via reconstructing the cytoskeleton and degrading the tumor basement membrane. Accumulating evidence shows that resveratrol, as a non-flavonoid polyphenol, can reverse EMT and inhibit invasion and migration of human tumors via diverse mechanisms and signaling pathways. In the present review, we will summarize the detailed mechanisms and pathways by which resveratrol and its analogs (e.g. Triacetyl resveratrol, 3,5,4′-Trimethoxystilbene) might regulate the EMT process in cancer cells to better understand their potential as novel anti-tumor agents. Resveratrol can also reverse chemoresistance via EMT inhibition and improvement of the antiproliferative effects of conventional treatments. Therefore, resveratrol and its analogs have the potential to become novel adjunctive agents to inhibit cancer metastasis, which might be partly related to their blocking of the EMT process.

Gastroesophageal junction (GEJ) was one of the most common malignant tumors. However, the value of clinicopathological features in predicting the prognosis of postoperative patients with GEJ cancer and without distant metastasis was still unclear.

The 3425 GEJ patients diagnosed and underwent surgical resection without distant metastasis in the Surveillance, Epidemiology and End Results (SEER) database from 2010 to 2015 were enrolled,and they were randomly divided into training and validation cohorts with 73 ratio. Univariate and multivariate Cox regression analysis were used to determine the predictive factors that constituted the nomogram. Talabostat solubility dmso The predictive accuracy and discriminability of Nomogram were determined by the area under the curve (AUC), C index, and calibration curve, and the influence of various factors on prognosis was explored.

2,400 patients were designed as training cohort and 1025 patients were designed as validation cohort. The percentages of the distribution of demographic and clinicodistant metastasis.

Glioma is one of the most common malignancies in the central nervous system and has limited effective therapeutic options. Therefore, we sought to identify a suitable target for immunotherapy.

We screened prognostic genes for glioma in the CGGA database and GSE43378 dataset using survival analysis, receiver operating characteristic (ROC) curves, independent prognostic analysis, and clinical correlation analysis. The results were intersected with immune genes from the ImmPort database through Venn diagrams to obtain likely target genes. The target genes were validated as prognostically relevant immune genes for glioma using survival, ROC curve, independent prognostic, and clinical correlation analyses in samples from the CGGA database and GSE43378 dataset, respectively. We also constructed a nomogram using statistically significant glioma prognostic factors in the CGGA samples and verified their sensitivity and specificity with ROC curves. The functions, pathways, and co-expression-related genes for the glioma target genes were assessed using PPI networks, enrichment analysis, and correlation analysis.