ArticleFrontiers in oncology2022
Identification and validation of an immunological microenvironment signature and prediction model for epstein-barr virus positive lymphoma: Implications for immunotherapy.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Epstein-Barr virus (EBV) is considered a carcinogenic virus, which is associated with high risk for poor prognosis in lymphoma patients, and there has been especially no satisfying and effective treatment for EBV+ lymphoma. We aimed to identify the immunological microenvironment molecular signatures which lead to the poor prognosis of EBV+ lymphoma patients. Methods: Differential genes were screened with microarray data from the GEO database (GSE38885, GSE34143 and GSE13996). The data of lymphoid neoplasm diffuse large B-cell lymphoma (DLBC) from the TCGA database and GSE4475 were used to identify the prognostic genes. The data of GSE38885, GSE34143, GSE132929, GSE58445 and GSE13996 were used to eluate the immune cell infiltration. Formalin-fixed, paraffin-embedded tissue was collected for Real Time Quantitative PCR from 30 clinical samples, including 15 EBV+ and 15 EBV- lymphoma patients. Results: Four differential genes between EBV+ and EBV- lymphoma patients were screened out with the significance of the survival and prognosis of lymphoma, including CHIT1, SIGLEC15, PLA2G2D and TMEM163. Using CIBERSORT to evaluate immune cell infiltration, we found the infiltration level of macrophages was significantly different between EBV+ and EBV- groups and was closely related to different genes. Preliminary clinical specimen verification identified that the expression levels of CHIT1 and TMEM163 were different between EBV+ and EBV- groups. Conclusions: Our data suggest that differences in expression levels of CHIT1 and TMEM163 and macrophage infiltration levels may be important drivers of poor prognosis of EBV+ lymphoma patients. These hub genes may provide new insights into the prognosis and therapeutic target for EBV+ lymphoma.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.