Evidence map›Paper›PMID 40456819›Full record

ArticleScientific reports2025

The 3D genome of plasma cells in multiple myeloma.

Kaiji Zhang, Mengsi Chen, Ming Chen, Yue Wang, Haibo Liu, Yanju Li, Xiaohong Guan, Lihua Lei, Li Tao, Xiaoxiao Liu and 2 more

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Kaiji ZhangDepartment of Hematology, Chengdu First People's Hospital, 18 Wanxiang North Road, Chengdu, 610016, China. zhangkaiji2024@163.com.
Mengsi ChenChengdu University of Traditional Chinese Medicine, Chengdu, China.
Ming ChenChengdu University of Traditional Chinese Medicine, Chengdu, China.
Yue WangChengdu University of Traditional Chinese Medicine, Chengdu, China.
Haibo LiuChengdu University of Traditional Chinese Medicine, Chengdu, China.
Yanju LiAffiliated Hospital of Guizhou Medical University, Guiyang, China.
Xiaohong GuanDepartment of Hematology, Chengdu First People's Hospital, 18 Wanxiang North Road, Chengdu, 610016, China.
Lihua LeiDepartment of Hematology, Chengdu First People's Hospital, 18 Wanxiang North Road, Chengdu, 610016, China.
Li TaoDepartment of Hematology, Chengdu First People's Hospital, 18 Wanxiang North Road, Chengdu, 610016, China.
Xiaoxiao LiuDepartment of Hematology, Chengdu First People's Hospital, 18 Wanxiang North Road, Chengdu, 610016, China.
Dong HeDepartment of Hematology, Chengdu First People's Hospital, 18 Wanxiang North Road, Chengdu, 610016, China.
Xiaoli FeiDepartment of Hematology, Chengdu First People's Hospital, 18 Wanxiang North Road, Chengdu, 610016, China.

Funding

The Science and Technology Department of Sichuan Province 2020YJ0438
6 · The paper itself

Abstract

Multiple myeloma (MM) is a hematological malignancy characterized by expanding clonal plasma cells in the bone marrow (BM) that produce monoclonal immunoglobulin. It is an incurable disease, accounting for about 10% of blood malignancies and the second most common hematologic malignancy. Therefore, in-depth research into the molecular mechanisms and therapeutic targets of the disease is crucial. For the first time, we performed high-throughput chromosome conformation capture (Hi-C) analysis of plasma cells in five multiple myeloma patients, and integrated it with genome resequencing and transcriptomic associated with genomic variation and gene expression. As a result, 19 specific TAD (Topologically Associating Domain) boundaries in MM samples related to the immune response and Wnt signaling pathways were identified. Additionally, Loop structures were also analyzed, revealing that promoter-enhancer-associated loops were the most prevalent. Genomic characteristics of MM patients were explored, identifying SNPs, InDels, and CNVs, with variations in the CDS region potentially affecting gene function. Transcriptome analysis showed differentially expressed genes in MM patients, mainly involved in p53 signaling and cell adhesion. Multi-omics analysis identified overlapping genes related to MM, including those involved in MHC class II protein complex assembly and antigen presentation. The study provides insights into the complex genomic and transcriptomic changes in MM plasma cells, potentially aiding in identifying therapeutic targets.

Indexed as

Genome, HumanMultiple MyelomaPlasma CellsAgedFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticGenomicsHumansMaleMiddle AgedPolymorphism, Single NucleotideTranscriptome3D genomeGenome resequencingMultiple myelomaPlasma cellTranscriptome

Identifiers

PMID40456819
PMCPMC12130518

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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.