Evidence map›Paper›PMID 35754837›Full record

ArticleFrontiers in genetics2022

Immunophenotypic Landscape and Prognosis-Related mRNA Signature in Diffuse Large B Cell Lymphoma.

Yanan Jiang, Huimeng Sun, Hong Xu, Xin Hu, Wenqi Wu, Yangyang Lv, Jinhuan Wang, Su Liu, Yixin Zhai, Linyan Tian and 2 more

Abstract read
In one paragraph

Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Review
  2. Spatial transcriptomics reveals prognostically LYZCancer immunology, immunotherapy : CII · 2025
    Article
  3. Article
  4. Article
  5. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Yanan JiangKey Laboratory of Cancer Prevention and Therapy, Department of Hematology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Huimeng SunKey Laboratory of Cancer Prevention and Therapy, Department of Hematology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Hong XuKey Laboratory of Cancer Prevention and Therapy, Department of Hematology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Xin HuKey Laboratory of Cancer Prevention and Therapy of Tianjin, Key Laboratory of Molecular Cancer Epidemiology, Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Wenqi WuKey Laboratory of Cancer Prevention and Therapy, Department of Hematology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Yangyang LvKey Laboratory of Cancer Prevention and Therapy, Department of Hematology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Jinhuan WangDepartment of Oncology, Institute of Urology, Second Hospital of Tianjin Medical University, Tianjin, China.
Su LiuKey Laboratory of Cancer Prevention and Therapy, Department of Hematology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Yixin ZhaiKey Laboratory of Cancer Prevention and Therapy, Department of Hematology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Linyan TianKey Laboratory of Cancer Prevention and Therapy, Department of Hematology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Yafei WangKey Laboratory of Cancer Prevention and Therapy, Department of Hematology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Zhigang ZhaoKey Laboratory of Cancer Prevention and Therapy, Department of Hematology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diffuse large B cell lymphoma (DLBCL) exhibits a tightly complexity immune landscape. In this study, we intended to identify different immune phenotype and to examine the immune related mRNA signature for clinical characteristic, therapeutic responsiveness as well as risk stratification and survival prediction in DLBCL. We identified two immune infiltration subtypes of DLBCL patients based on 28 immune cell types. GSEA analysis uncovered the concordant classification of two robust significant subtypes of DLBCL. Considering the convenient application of the immune infiltration subtypes for prognostic prediction, we developed a risk score based on the differentially expressed genes between the Immunity-H and Immunity-L groups. By a least absolute shrinkage and selection operator (LASSO)-Cox regression model, a sixteen-gene risk signature, comprising ANTXR1, CD3D, TIMP1, FPR3, NID2, CTLA4, LPAR6, GPR183, LYZ, PTGDS, ITK, FBN1, FRMD6, PLAU, MICAL2, C1S, was established. The comprehensive results showed that the high-risk group was correlated with lower immune infiltration, more aggressive phenotypes, lower overall survival and more sensitive to lenalidomide. In contrast, a low-risk group score was associated with higher immune infiltration, less aggressive phenotypes, better overall survival and more likely to benefit from PD-1/PD-L1 inhibitors. Finally, a nomogram comprised of the risk score and IPI score was verified to more accurately predict the overall survival of DLBCL than traditional clinical prediction models. Altogether, our data demonstrate the heterogeneity of immune patterns within DLBCL and deepen our molecular understanding of this tumor entity.

Indexed as

diffuse large B cell lymphomaimmune risk signatureimmunotherapymRNA expressionprognosistumorinfiltrating lymphocytes

Identifiers

PMID35754837
PMCPMC9214219

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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.