Evidence map›Paper›PMID 36224623›Full record

ArticleCancer & metabolism2022

Scaffold-mediated switching of lymphoma metabolism in culture.

Rachana Bhatt, Dashnamoorthy Ravi, Andrew M Evens, Biju Parekkadan

Abstract read
In one paragraph

Article in Cancer & metabolism, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Metabolic Reprogramming and Potential Therapeutic Targets in Lymphoma.International journal of molecular sciences · 2023
    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

4 authors.

Rachana BhattDepartment of Biomedical Engineering, Rutgers, The State University of New Jersey, New Brunswick, NJ, USA.
Dashnamoorthy RaviDivision of Blood Disorders, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA.
Andrew M EvensDivision of Blood Disorders, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA.
Biju ParekkadanDepartment of Biomedical Engineering, Rutgers, The State University of New Jersey, New Brunswick, NJ, USA. biju.parekkadan@rutgers.edu.ORCID http://orcid.org/0000-0002-3408-8085

Funding

Artificial, Humanized Stem Cell NichesR01EB012521 · NIBIB · RUTGERS, THE STATE UNIV OF N.J. · PI PAREKKADAN, BIJU · 2011 to 2021
$6.0M
NIBIB NIH HHS R01 EB012521NIH HHS R01EB012521
6 · The paper itself

Abstract

backgroundDiffuse large B cell lymphoma (DLBCL) is an aggressive subtype of non-Hodgkin lymphoma (NHL) and accounts for about a third of all NHL cases. A significant proportion (~40%) of treated DLBCL patients develop refractory or relapsed disease due to drug resistance which can be attributed to metabolomic and genetic variations amongst diverse DLBCL subtypes. An assay platform that reproduces metabolic patterns of DLBCL in vivo could serve as a useful model for DLBCL.

methodsThis report investigated metabolic functions in 2D and 3D cell cultures using parental and drug-resistant DLBCL cell lines as compared to patient biopsy tissue.

resultsA 3D culture model controlled the proliferation of parental and drug-resistant DLBCL cell lines, SUDHL-10, SUDHL-10 RR (rituximab resistant), and SUDHL-10 OR (obinutuzumab resistant), as well as retained differential sensitivity to CHOP. The results from metabolic profiling and isotope tracer studies with D-glucose-

conclusion3D culture restrained DLBCL cell line growth and modulated metabolic pathways that trend towards the biological characteristics of patient tumors. Counter-intuitively, this research thereby contends that 3D matrices can be a tool to control tumor function towards a slower growing and metabolically dormant state that better reflects in vivo tumor physiology.

Indexed as

3D modelDLBCLDrug sensitivityLymphomaMetabolic fluxProliferation

Identifiers

PMID36224623
PMCPMC9559005

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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.