Transcriptome integration analysis and specific diagnosis model construction for Hodgkin's lymphoma, diffuse large B-cell lymphoma, and mantle cell lymphoma

Abstract

Transcriptome differences between Hodgkin's lymphoma (HL), diffuse large B-cell lymphoma (DLBCL), and mantle cell lymphoma (MCL), which are all derived from B cell, remained unclear. This study aimed to construct lymphoma-specific diagnostic models by screening lymphoma marker genes. Transcriptome data of HL, DLBCL, and MCL were obtained from public databases. Lymphoma marker genes were screened by comparing cases and controls as well as the intergroup differences among lymphomas. A total of 9 HL marker genes, 7 DLBCL marker genes, and 4 MCL marker genes were screened in this study. Most HL marker genes were upregulated, whereas DLBCL and MCL marker genes were downregulated compared to controls. The optimal HL-specific diagnostic model contains one marker gene (MYH2) with an AUC of 0.901. The optimal DLBCL-specific diagnostic model contains 7 marker genes (LIPF, CCDC144B, PRO2964, PHF1, SFTPA2, NTS, and HP) with an AUC of 0.951. The optimal MCL-specific diagnostic model contains 3 marker genes (IGLV3-19, IGKV4-1, and PRB3) with an AUC of 0.843. The present study reveals the transcriptome data-based differences between HL, DLBCL, and MCL, when combined with other clinical markers, may help the clinical diagnosis and prognosis.

Integrated analysis of 14 lymphoma datasets revealed high expression of CXCL14 promotes cell migration in mantle cell lymphoma

“…The details of lymphoma datasets see our previous publication [ 19 ]. This study collected 240 HL samples, 891 DLBCL samples, 216 MCL samples, and 64 health samples.…”

“…Transcriptome datasets of HL, DLBCL, and MCL were downloaded from NCBI-GEO ( https://www.ncbi.nlm.nih.gov/geo/ ). For detailed data inclusion and exclusion criteria, please refer to our previous work [ 19 ]. Briefly, this study collected 14 lymphoma datasets including 240 HL samples, 891 DLBCL samples, 216 MCL samples, and 64 healthy samples.…”

“…R statistical software v3.4.1 ( https://www.r-project.org/ ) was used to perform data preprocessing and differential gene expression gene analysis. The data preprocessing process has been described in detail in our previous work [ 19 ]. The empirical Bayesian algorithm in the limma package [ 43 ] was used to detect differentially expressed genes between lymphoma patients and controls.…”

DIA-Based Proteomic Analysis of Plasma Protein Profiles in Patients with Severe Acute Pancreatitis

“…However, patients with SAP may develop immunosuppression, resulting in pancreatic necrosis and secondary infection [23,24]. IGKV4-1 is involved in the protection of acute rejection and considered an effective biomarker for the early identification of mantle cell lymphoma [25,26]. IGHG3, which is also involved in acute rejection [27], may contribute to platelet activation during ischemic stroke, and it is expected to be a potential target for the treatment of the early phase of stroke [28].…”