The Expression of CD30 Based on Immunohistochemistry Predicts Inferior Outcome in Patients with Diffuse Large B-Cell Lymphoma

<div><p>The prognostic value of CD30 expression indiffuse large B-cell lymphoma (DLBCL)remains controversial. Herein, we performed this retrospective study to investigate the clinical and prognostic significance of CD30 expression in patients with DLBCL.Among all the 146 patients, the expression of CD30 was observed in 23 cases (15.7%).The DLBCL patients with CD30 expression showed more likely to present B symptoms, bone marrow involvement, non-germinal centre B-cell-like (Non-GCB) DLBCL, BCL-2 and Ki-67overexpression(p<0.05). Patients with CD30 expression showed significantly poor overall and event-free survivalcompared with CD30 negative patients(p = 0.031 and 0.041, respectively), especially those with the high intermediate/high-risk international prognostic index (IPI)(p = 0.001 and 0.007, respectively). The prognostic value of CD30expression retained in DLBCL patients treated with eitherCHOP (cyclophosphamide, doxorubicin, vincristine,prednisone) or R-CHOP(rituximab+CHOP). The multivariate analysisrevealed that the expression of CD30 remained an unfavorable factor for both overall and event-free survival (p = 0.001 and 0.002, respectively).In conclusion, these data suggest that CD30 is expressed predominantly in Non-GCBDLBCL. The expression of CD30 implied poor outcomein DLBCL patientstreated with either CHOP or R-CHOP, especially those with the high intermediate/high-risk IPI, possibly indicating that anti-CD30 monoclonal antibody could be of clinical interest.</p></div

Multivariate Cox regression analysis for survival.

<p>LDH, Lactate dehydrogenase; IPI,internationalprognosticindex; HR, hazard ratio</p><p>95%CI, 95confidence interval</p><p>Multivariate Cox regression analysis for survival.</p

Clinical characteristics of patients according to CD30 expression.

<p>LDH, Lactate dehydrogenase; BM, bone marrow;IPI,internationalprognosticindex</p><p>COO, cell of origin;GCB,germinal center B-cell like.</p><p>Clinical characteristics of patients according to CD30 expression.</p

DataSheet_1_Construction and validation of a prognostic model for hepatocellular carcinoma: Inflammatory ferroptosis and mitochondrial metabolism indicate a poor prognosis.zip

BackgroundAn increasing number of innovations have been discovered for treating hepatocellular carcinoma (HCC or commonly called HCC) therapy, Ferroptosis and mitochondrial metabolism are essential mechanisms of cell death. These pathways may act as functional molecular biomarkers that could have important clinical significance for determining individual differences and the prognosis of HCC. The aim of this study was to construct a stable and reliable comprehensive model of genetic features and clinical factors associated with HCC prognosis.MethodsIn this study, we used RNA-sequencing (fragments per kilobase of exon model per million reads mapped value) data from the Cancer Genome Atlas (TCGA) database to establish a prognostic model. We enrolled 104 patients for further validation. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes enrichment analyses (KEGG) analysis were used for the functional study of differentially expressed genes. Pan-cancer analysis was performed to evaluate the function of the Differentially Expressed Genes (DEGs). Thirteen genes were identified by univariate and least absolute contraction and selection operation (LASSO) Cox regression analysis. The prognostic model was visualized using a nomogram.ResultsWe found that eight genes, namely EZH2, GRPEL2, PIGU, PPM1G, SF3B4, TUBG1, TXNRD1 and NDRG1, were hub genes for HCC and differentially expressed in most types of cancer. EZH2, GRPEL2 and NDRG1 may indicate a poor prognosis of HCC as verified by tissue samples. Furthermore, a gene set variation analysis algorithm was created to analyze the relationship between these eight genes and oxidative phosphorylation, mitophagy, and FeS-containing proteins, and it showed that ferroptosis might affect inflammatory-related pathways in HCC.ConclusionEZH2, GRPEL2, NDRG1, and the clinical factor of tumor size, were included in a nomogram for visualizing a prognostic model of HCC. This nomogram based on a functional study and verification by clinical samples, shows a reliable performance of patients with HCC.</p

Kaplan-Meier curve for overall survival (OS) and event-free survival (EFS) according to the expression of CD30 and IPI.

<p>OS (A) and EFS (B) for high intermediate/high IPI risk patients (IPI = 3–5) with and without CD30 expression; OS (C) and EFS (D) for low/ low intermediate risk IPIpatients (IPI = 0–2)with and without CD30 expression.</p

Kaplan-Meier curve for overall survival (OS) and event-free survival (EFS) according to the expression of CD30 and treatment.

<p>OS (<b>A</b>) and EFS (<b>B</b>) according to CD30 expression in DLBCL patients treated with CHOP. OS (<b>C</b>) and EFS (<b>D</b>) according to CD30 expression in DLBCL patients treated with R-CHOP.</p

Kaplan-Meier curve of overall survival (A) and event-free survival (B) in DLBCL patients according to CD30 expression.

<p>Kaplan-Meier curve of overall survival (A) and event-free survival (B) in DLBCL patients according to CD30 expression.</p

Image_1_Construction and validation of a prognostic model for hepatocellular carcinoma: Inflammatory ferroptosis and mitochondrial metabolism indicate a poor prognosis.pdf

BackgroundAn increasing number of innovations have been discovered for treating hepatocellular carcinoma (HCC or commonly called HCC) therapy, Ferroptosis and mitochondrial metabolism are essential mechanisms of cell death. These pathways may act as functional molecular biomarkers that could have important clinical significance for determining individual differences and the prognosis of HCC. The aim of this study was to construct a stable and reliable comprehensive model of genetic features and clinical factors associated with HCC prognosis.MethodsIn this study, we used RNA-sequencing (fragments per kilobase of exon model per million reads mapped value) data from the Cancer Genome Atlas (TCGA) database to establish a prognostic model. We enrolled 104 patients for further validation. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes enrichment analyses (KEGG) analysis were used for the functional study of differentially expressed genes. Pan-cancer analysis was performed to evaluate the function of the Differentially Expressed Genes (DEGs). Thirteen genes were identified by univariate and least absolute contraction and selection operation (LASSO) Cox regression analysis. The prognostic model was visualized using a nomogram.ResultsWe found that eight genes, namely EZH2, GRPEL2, PIGU, PPM1G, SF3B4, TUBG1, TXNRD1 and NDRG1, were hub genes for HCC and differentially expressed in most types of cancer. EZH2, GRPEL2 and NDRG1 may indicate a poor prognosis of HCC as verified by tissue samples. Furthermore, a gene set variation analysis algorithm was created to analyze the relationship between these eight genes and oxidative phosphorylation, mitophagy, and FeS-containing proteins, and it showed that ferroptosis might affect inflammatory-related pathways in HCC.ConclusionEZH2, GRPEL2, NDRG1, and the clinical factor of tumor size, were included in a nomogram for visualizing a prognostic model of HCC. This nomogram based on a functional study and verification by clinical samples, shows a reliable performance of patients with HCC.</p