Evidence map›Paper›PMID 39137931›Full record

ArticleBritish journal of haematology2024

Prognostic stratification in DLBCL patients with aberrant MYC gene.

Jian-Rong Li, Vikram R Shaw, Abi Parthasarathy, Yong Li, Christopher I Amos, Chao Cheng

Abstract read
In one paragraph

Article in British journal of haematology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Jian-Rong LiInstitute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas, USA.
Vikram R ShawInstitute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas, USA.
Abi ParthasarathyInstitute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas, USA.
Yong LiSection of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA.
Christopher I AmosInstitute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas, USA.
Chao ChengInstitute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas, USA.ORCID https://orcid.org/0000-0002-5002-3417

Funding

(PQD4) SIGNS OF INFLAMMATORY BREAST CANCER ARE CAUSED BY STROMAL FIELD EFFECTSR01CA180061 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI WOODWARD, WENDY A · 2013 to 2016
$1.9M
An innovative integrated computational framework using gene signatures for patient stratificationR01CA269764 · NCI · BAYLOR COLLEGE OF MEDICINE · PI CHAO CHENG · 2023 to 2026
$1.8M
High Memory High-Performance Computer Cluster for Biomedical ResearchS10OD032185 · OD · BAYLOR COLLEGE OF MEDICINE · PI HILSENBECK, SUSAN G. · 2022 to 2022
$596k
Cancer Prevention and Research Institute of Texas RR180061Center for Biomedical Informatics and Information Technology 1R01CA269764NCI NIH HHS R01 CA269764NIH HHS S10 OD032185
6 · The paper itself

Abstract

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease characterized by a subset of patients who exhibit treatment resistance and poor prognoses. Genomic assays have been widely employed to identify high-risk individuals characterized by rearrangements in the MYC, BCL2 and BCL6 genes. These patients typically undergo more aggressive therapeutic treatments; however, there remains a significant variation in their treatment outcomes. This study introduces an MYC signature score (MYCSS) derived from gene expression profiles, specifically designed to evaluate MYC overactivation in DLBCL patients. MYCSS was validated across several independent cohorts to assess its ability to stratify patients based on MYC-related genetic and molecular aberrations, enhancing the accuracy of prognostic evaluations compared to conventional MYC biomarkers. Our results indicate that MYCSS significantly refines prognostic accuracy beyond that of conventional MYC biomarkers focused on genetic aberrations. More importantly, we found that nearly 50% of patients identified as high risk by traditional MYC metrics actually share similar survival prospects with those having no MYC aberrations. These patients may benefit from standard GCB-based therapies rather than more aggressive treatments. MYCSS provides a robust signature that identifies high-risk patients, aiding in the precision treatment of DLBCL, and minimizing the potential for overtreatment.

Indexed as

Lymphoma, Large B-Cell, DiffuseProto-Oncogene Proteins c-mycAdultAgedBiomarkers, TumorFemaleGene Expression ProfilingGenes, mycHumansMaleMiddle AgedPrognosisBiomarkers, TumorMYC protein, humanProto-Oncogene Proteins c-mycdiffuse large B‐cell lymphomagene signaturesMYC rearrangementprognostic stratification

Identifiers

PMID39137931
PMCPMC11568942

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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.