Evidence map›Paper›PMID 32589729›Full record

ArticleBlood advances2020

CRISPR-based screens uncover determinants of immunotherapy response in multiple myeloma.

Poornima Ramkumar, Anthony B Abarientos, Ruilin Tian, Meghan Seyler, Jaime T Leong, Merissa Chen, Priya Choudhry, Torsten Hechler, Nina Shah, Sandy W Wong and 7 more

Open access · goldAbstract read
In one paragraph

Article in Blood advances, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed
2.8field-weighted citation impact, top 8% of its field
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

41 citing papers in PubMed, 58 citations in OpenAlex.

  1. Review
  2. Epigenetic insights and innovations for overcoming barriers in CAR-T cell therapy for cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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  10. Genotype from Phenotype: Using CRISPR Screens to Dissect Lymphoma Biology.Methods in molecular biology (Clifton, N.J.) · 2025
    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

17 authors at 2 institutions in 2 countries.

Poornima RamkumarInstitute for Neurodegenerative Diseases and.
Anthony B AbarientosInstitute for Neurodegenerative Diseases and.
Ruilin TianInstitute for Neurodegenerative Diseases and.
Meghan SeylerInstitute for Neurodegenerative Diseases and.
Jaime T LeongInstitute for Neurodegenerative Diseases and.
Merissa ChenInstitute for Neurodegenerative Diseases and.
Priya ChoudhryDepartment of Laboratory Medicine, University of California, San Francisco, CA.
Torsten HechlerHeidelberg Pharma, Ladenburg, Germany.
Nina ShahDivision of Hematology/Oncology, Department of Medicine, and.
Sandy W WongDivision of Hematology/Oncology, Department of Medicine, and.
Thomas G MartinDivision of Hematology/Oncology, Department of Medicine, and.
Jeffrey L WolfDivision of Hematology/Oncology, Department of Medicine, and.
Kole T RoybalDepartment of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA.
Andreas PahlHeidelberg Pharma, Ladenburg, Germany.
Jack TauntonDepartment of Cellular and Molecular Pharmacology, and.
Arun P WiitaDepartment of Laboratory Medicine, University of California, San Francisco, CA.
Martin KampmannInstitute for Neurodegenerative Diseases and.
German Center for Neurodegenerative Diseases · DEUniversity of California, San Francisco · US

Funding

In vivo monitoring of oxidative protein folding through time-resolved quantitative mass spectrometryDP2GM123500 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WIITA, ARUN P. · 2016 to 2016
$1.9M
Exploiting myeloma proteome remodeling to extend proteasome inhibitor efficacyR01CA226851 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WIITA, ARUN P. · 2018 to 2022
$1.6M
Stress response networks in cancer: systematic mapping and therapeutic potentialR00CA181494 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KAMPMANN, MARTIN · 2015 to 2017
$747k
Stress response networks in cancer: systematic mapping and therapeutic potentialK99CA181494 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KAMPMANN, MARTIN · 2014 to 2014
$139k
NCI NIH HHS K99 CA181494NCI NIH HHS R00 CA181494NCI NIH HHS R01 CA226851NIGMS NIH HHS DP2 GM123500
6 · The paper itself

Abstract

Cancer cells commonly develop resistance to immunotherapy by loss of antigen expression. Combinatorial treatments that increase levels of the target antigen on the surface of cancer cells have the potential to restore efficacy to immunotherapy. Here, we use our CRISPR interference- and CRISPR activation-based functional genomics platform to systematically identify pathways controlling cell surface expression of the multiple myeloma immunotherapy antigen B-cell maturation antigen (BCMA). We discovered that pharmacologic inhibition of HDAC7 and the Sec61 complex increased cell surface BCMA, including in primary patient cells. Pharmacologic Sec61 inhibition enhanced the antimyeloma efficacy of a BCMA-targeted antibody-drug conjugate. A CRISPR interference chimeric antigen receptor T cells (CAR-T cells) coculture screen enabled us to identify both antigen-dependent and antigen-independent mechanisms controlling response of myeloma cells to BCMA-targeted CAR-T cells. Thus, our study shows the potential of CRISPR screens to uncover mechanisms controlling response of cancer cells to immunotherapy and to suggest potential combination therapies.

Indexed as

B-Cell Maturation AntigenMultiple MyelomaClustered Regularly Interspaced Short Palindromic RepeatsHumansImmunotherapyImmunotherapy, AdoptiveT-LymphocytesB-Cell Maturation Antigen

Identifiers

PMID32589729
PMCPMC7362346
OpenAlexW3037236323

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.