Evaluation of latent membrane protein 1 and microRNA‑155 for the prognostic prediction of diffuse large B cell lymphoma

Abstract

Diffuse large B cell lymphoma (DLBCL) has previously been demonstrated to contribute to the mortality of lymphoma with various aggressive features. The prognostic role of the biomarkers latent membrane protein (LMP) 1 and microRNA-(miR)-155 in DLBCL remain controversial. The present study primarily aimed to assess the effect of LMP1 and miR-155 on the survival of DLBCL patients, and additionally evaluate the clinical features to observe their influence on outcomes, compared with previous studies. Formalin-fixed and paraffin-embedded samples were collected from our center between May 2010 and December 2011. Microarray analysis, immunohistochemical analysis and reverse transcription-quantitative polymerase chain reaction were used to evaluate the expression of LMP1 and miR-155. The association between biomarkers or clinical features and patient outcomes was assessed using the log-rank statistical test, Cox proportional hazard model and Kaplan-Meier method. SPSS software was used to statistically analyze the data. A total of 82 patients were included in the present study. The results demonstrated that high expression of LMP1 and miR-155 may be associated with a poor progression-free survival rate, while a high International Prognostic Index score and high expression of LMP1 may be associated with a poor overall survival rate. These results indicated that LMP1 and miR-155 may be novel and reliable biomarkers for the prognostic prediction of lymphoma, and will potentially be analyzed in the future to evaluate patient prognosis.

MicroRNA and Other Non-Coding RNAs in Epstein–Barr Virus-Associated Cancers

“…EBV contributes to DLBCL by regulating key cell signaling pathways through its viral proteins and miRNAs. For instance, LMP1 is able to increase miR-34a, -146a, and -155 expression via the NF-κB pathway, while BART3, BART9, and BART17-5p can downregulate BCL6 and thereby increase NF-κB activation [135][136][137][138].…”

Prediction of protein structural classes by different feature expressions based on 2-D wavelet denoising and fusion

“…Through related experiments, we not only verify the effect of the wavelet denoising algorithm on the models but also compare the overall accuracy of our models with those of other methods. Ultimately, we can conclude that our method is good for predicting the structural classes of protein sequences and is expected to be applied in other fields related to bioinformatics [61–74]. The related source codes and datesets are available at https://github.com/Xiaoheng-Wang12/Wang-xiaoheng/tree/master.…”

Hubungan Ekspresi LMP-1 dengan Overall Survival Pasien Diffuse Large B-Cell Lymphoma di RSUP Dr Kariadi Semarang

“…9 Temuan penelitian ini sejalan dengan beberapa literatur yang melaporkan pemendekan survival pada pasien-pasien DLBCL yang mengekspresikan LMP1. [2][3][4][5][6][9][10][11] Beberapa kemungkinan mekanisme yang mendasari hal ini adalah LMP1 mampu mencetuskan pertumbuhan sel-sel tumor secara keseluruhan, invasif dan kemudahan dalam bermetastasis melalui aktivasi jalur NF-kB, JNK/p38-SAPK, PI3K/AKT, ERK-MAPK dan JAK/STAT. LMP1 mampu menginduksi Matrix Metallo Proteinase (MMP) sehingga mencetuskan modulasi interaksi matriks sel dan mengakibatkan mudahnya invasi sel tumor.…”