Evidence map›Paper›PMID 39567630›Full record

ArticleScientific reports2024

Cell surface marker heterogeneity in human myeloma cell lines for modeling of disease and therapy.

Alenka Djarmila Behsen, Toril Holien, Francesca Micci, Morten Rye, Jenny Malm Rasmussen, Kristin Andersen, Eli Svorkdal Hess, Magne Børset, Jonathan Keats, Thea Kristin Våtsveen and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

11 authors.

Alenka Djarmila Behsen *Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Toril Holien *Department of Biomedical Laboratory Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Francesca MicciSection for Cancer Cytogenetics, Institute for Cancer Genetics and Informatics, The Norwegian Radium Hospital, Oslo University Hospital, Oslo, Norway.
Morten RyeDepartment of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Jenny Malm RasmussenDepartment of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Kristin AndersenSection for Cancer Cytogenetics, Institute for Cancer Genetics and Informatics, The Norwegian Radium Hospital, Oslo University Hospital, Oslo, Norway.
Eli Svorkdal HessDepartment of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Magne BørsetDepartment of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Jonathan KeatsIntegrated Cancer Genomics Division, Translational Genomics Research Institute (TGen), Phoenix, AZ, USA.
Thea Kristin VåtsveenK.G. Jebsen Centre for B Cell Malignancies, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Kristine MisundDepartment of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway. kristine.misund@ntnu.no.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple myeloma (MM) is a hematological malignancy originating from plasma cells. Genetically, MM is categorized into two subtypes: hyperdiploid and non-hyperdiploid tumors, with distinct chromosomal characteristics. Human myeloma cell lines (HMCLs) are instrumental in understanding MM and identifying therapeutic targets. However, their utility depends on their resemblance to patient-derived cells. We analyzed protein expression of cell surface markers, including myeloma drug targets and immunotherapy-relevant markers, in nine HMCLs using flow cytometry. RNAseq analysis was performed to correlate protein expression with transcriptomic data. While five cell surface markers (CD47, CD49d, CD138, CD269 (BCMA), and GPRC5D) were highly expressed and three (CD19, CD20, and CD117) were low or negative across cell lines, heterogenous expression was observed for the 16 remaining markers. A comparative study with patient-derived transcriptomic data indicated that four of our six in-house HMCLs closely resembled patient disease. Furthermore, our hyperdiploid HMCLs correlated better with hyperdiploid than non-hyperdiploid patient samples. Here, we also describe three previously uncharacterized HMCLs; IH-1, URVIN and FOLE. Our findings underscore the importance of evaluating surface protein expression in HMCLs when modeling MM. The observed variations in expression levels emphasize the need for a strategic selection of cell lines based on the study's objectives.

Indexed as

Biomarkers, TumorMultiple MyelomaCell Line, TumorFlow CytometryGene Expression Regulation, NeoplasticHumansTranscriptomeBiomarkers, Tumor

Identifiers

PMID39567630
PMCPMC11579509

What Socratic holds

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Registered trials

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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 Socratic graph.