Our research was aimed to identify the expression, clinical value and biological significance of GINS complex subunit 4 (GINS4) in hepatocellular carcinoma (HCC).
GINS4 was initially screened through weighted gene co-expression network analysis (WGCNA). The TCGA, GEO, and TIMER databases were applied for analyzing the GINS4 mRNA expression in HCC. GINS4 protein levels were detected
immunohistochemistry (IHC). Receiver operating characteristic (ROC) curve was applied for estimating the diagnostic significance of GINS4 in HCC. Kaplan-Meier plots, Cox model, and nomogram were used to assess the prognostic performance of GINS4 in HCC. learn more Nomogram validation was conducted through time-dependent ROC and decision curve analysis (DCA). The Wanderer, UALCAN, and DiseaseMeth databases were utilized to identify GINS4 methylation levels in HCC. Genes co-expressed with GINS4 in HCC were estimated through the TCGA, cBioPortal, and GEPIA. GO, KEGG, and GSEA unraveled the possible biological mechanisms of GINS4 in HCC.
with undesirable survival of HCC patients.
GINS4 is overexpressed in HCC and is correlated with undesirable survival of HCC patients.
Cancer has been suggested as a risk factor for severe outcome of SARS-CoV-2 infection. In this population-based study we aimed to identify factors associated with higher risk of COVID-19 and adverse outcome.
Data on all confirmed SARS-CoV-2 positive patients in the period January 1 to May 31, 2020 were extracted from the Norwegian Surveillance System for Communicable Diseases. Data on cancer and treatment was available from the Cancer Registry of Norway, the Norwegian Patient Registry and the Norwegian Prescription Database. Deaths due to COVID-19 were extracted from the Cause of Death Registry. From the Norwegian Intensive Care and Pandemic Registry we retrieved data on admittance to hospital and intensive care. We determined rates of COVID-19 disease in cancer patients and the rest of the population. We also ran multivariate analyses adjusting for age andgender.
A total of 8 410 patients were diagnosed with SARS-CoV-2 infection in Norway during the study period, of which 547 (6.5%) were cancer patient2.60-33.34). For the combined outcome death and/or admittance to hospital due to COVID-19, we found significant two-fold increased risk estimates for patients diagnosed with cancer less than one 1 year ago (OR 2.08, 95% CI 1.14-3.80), for those treated with anti-cancer drugs during the past 3 months (OR 1.80, 95% CI 1.07-3.01) and for patients undergoing major surgery during the past 3 months (OR 2.19, 95% CI 1.40-3.44).
Autophagy related protein 5 (ATG5) is an important autophagosome formation related protein, and its involvement in the biological process of autophagy has been shown to correlate with tumor metabolic patterns and the formation of tumor heterogeneity. However, the role of ATG5 in tumor metabolism and tumor immunity remains unclear.
In order to explore this problem, this study was designed to reveal the role of ATG5 in tumor metabolism and tumor immunity through pan-cancer analysis of multi-database. GTEx database, CCLE database, and TCGA database were used to describe the expression, prognosis, immune microenvironment, immune new antigen, immune checkpoint, TMB, and microsatellite instability of ATG5 in 33 types of tumors. A series of bioinformatics tools and methods were used for quantitative analysis and panoramic description, such as to Estimate, Scanneo and GSEA.
The differential analysis results of multiple databases showed that ATG5 was ubiquitously highly expressed in pan-cancer, especially in solide, and played an important role in tumor metabolism and tumor immunity. The comprehensive pan-cancer analysis not only revealed the potential of ATG5 in tumor-targeted therapy but also suggested ATG5 as a promising tumor predictive biomarker in most solid tumors.
ATG5 participated in the formation of autophagosomal membrane important molecule LC3-II outside, and played an important role in tumor metabolism and tumor immunity. The comprehensive pan-cancer analysis not only revealed the potential of ATG5 in tumor-targeted therapy but also suggested ATG5 as a promising tumor predictive biomarker in most solid tumors.CAR T-cell therapy has revolutionized the treatment approach to patients with relapsed/refractory hematologic malignancies; however, there continues to be opportunity for improvement in treatment toxicity as well as response durability. Radiation therapy can play an important role in combined modality treatments for some patients undergoing CAR T-cell therapy in various clinical settings. In this review, we discuss the current evidence for RT in the setting of CAR T-cell therapy for patients with hematologic malignancies and propose potential opportunities for future investigation of RT and CAR T-cell treatment synergy. Future research frontiers include investigation of hypotheses including radiation priming of CAR T-cell mediated death, pre-CAR T-cell tumor debulking with radiation therapy, and selection of high risk patients for early radiation salvage after CAR T cell therapy.
Renal medullary carcinoma (RMC) is a rare but aggressive tumor often complicated by early lung metastasis with few treatment options and very poor outcomes. There are currently no verified RMC patient-derived xenograft (PDX) mouse models established from metastatic pleural effusion (PE) available to study RMC and evaluate new therapeutic options.
Renal tumor tissue and malignant PE cells from an RMC patient were successfully engrafted into 20 NOD.Cg-Prkdc
Il2rg
/SzJ (NSG) mice. We evaluated the histopathological similarity of the renal tumor and PE PDXs with the original patient renal tumor and PE, respectively. We then evaluated the molecular integrity of the renal tumor PDXs between passages, as well as the PE PDX compared to two generations of renal tumor PDXs, by microarray analysis. The therapeutic efficacy of sunitinib and temsirolimus was tested in a serially-transplanted generation of 27 PE PDXmice.
The pathologic characteristics of the patient renal tumor and patient PE were retained in the PDXs.learn more
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