Evidence map›Paper›PMID 39050513›Full record

ArticleCellular and molecular bioengineering2024

Dynamic Transcriptional Programs During Single NK Cell Killing: Connecting Form to Function in Cellular Immunotherapy.

Joseph T Decker, Matthew S Hall, Devak Nanua, Sophia M Orbach, Jyotirmoy Roy, Amogh Angadi, Julianna Caton, Lauren Hesse, Jacqueline S Jeruss, Lonnie D Shea

Abstract read
In one paragraph

Article in Cellular and molecular bioengineering, 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

10 authors.

Joseph T DeckerDepartment of Biomedical Engineering, University of Michigan, 1600 Huron Parkway, Ann Arbor, MI 48109 USA.ORCID 0000-0001-7914-4741
Matthew S HallDepartment of Biomedical Engineering, University of Michigan, 1600 Huron Parkway, Ann Arbor, MI 48109 USA.
Devak NanuaDepartment of Biomedical Engineering, University of Michigan, 1600 Huron Parkway, Ann Arbor, MI 48109 USA.
Sophia M OrbachDepartment of Biomedical Engineering, University of Michigan, 1600 Huron Parkway, Ann Arbor, MI 48109 USA.
Jyotirmoy RoyDepartment of Biomedical Engineering, University of Michigan, 1600 Huron Parkway, Ann Arbor, MI 48109 USA.
Amogh AngadiDepartment of Biomedical Engineering, University of Michigan, 1600 Huron Parkway, Ann Arbor, MI 48109 USA.
Julianna CatonDepartment of Biomedical Engineering, University of Michigan, 1600 Huron Parkway, Ann Arbor, MI 48109 USA.
Lauren HesseDepartment of Biomedical Engineering, University of Michigan, 1600 Huron Parkway, Ann Arbor, MI 48109 USA.
Jacqueline S JerussDepartment of Biomedical Engineering, University of Michigan, 1600 Huron Parkway, Ann Arbor, MI 48109 USA.
Lonnie D SheaDepartment of Biomedical Engineering, University of Michigan, 1600 Huron Parkway, Ann Arbor, MI 48109 USA.

Funding

Identifying intercellular circuits driving cell phenotypes within a nicheR01CA243916 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI JERUSS, JACQUELINE SARA, SHEA, LONNIE D · 2019 to 2023
$2.3M
Chimeric Antigen Receptor T Cell Design Through Living Cell Systems BiologyK01EB028877 · NIBIB · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DECKER, JOSEPH THOMAS · 2019 to 2022
$492k
Engineering Natural Killer Cell Homing and Activation at the Metastatic NicheF32CA228262 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI HALL, MATTHEW STEVEN · 2018 to 2020
$163k
NCI NIH HHS F32 CA228262NCI NIH HHS R01 CA243916NIBIB NIH HHS K01 EB028877
6 · The paper itself

Abstract

Introduction: Natural killer (NK) cell-based therapies are a promising new method for treating indolent cancer, however engineering new therapies is complex and progress towards therapy for solid tumors is slow. New methods for determining the underlying intracellular signaling driving the killing phenotype would significantly improve this progress. Methods: We combined single-cell RNA sequencing with live cell imaging of a model system of NK cell killing to correlate transcriptomic data with functional output. A model of NK cell activity, the NK-92 cell line killing of HeLa cervical cancer cells, was used for these studies. NK cell killing activity was observed by microscopy during co-culture with target HeLa cells and killing activity subsequently manually mapped based on NK cell location and Annexin V expression. NK cells from this culture system were profiled by single-cell RNA sequencing using the 10× Genomics platform, and transcription factor activity inferred using the Viper and DoRothEA R packages. Luminescent microscopy of reporter constructs in the NK cells was then used to correlate activity of inferred transcriptional activity with killing activity. Results: NK cells had heterogeneous killing activity during 10 h of culture with target HeLa cells. Analysis of the single cell sequencing data identified Nuclear Factor Kappa B (NF-κB), Signal Transducer and Activator of Transcription 1 (STAT1) and MYC activity as potential drivers of NK cell functional phenotype in our model system. Live cell imaging of the transcription factor activity found NF-κB activity was significantly correlated with past killing activity. No correlation was observed between STAT1 or MYC activity and NK cell killing. Conclusions: Combining luminescent microscopy of transcription factor activity with single-cell RNA sequencing is an effective means of assigning functional phenotypes to inferred transcriptomics data. Supplementary Information: The online version contains supplementary material available at 10.1007/s12195-024-00812-3.

Indexed as

Cell-based immunotherapyLive-cell imagingNK cellTranscriptomics

Identifiers

PMID39050513
PMCPMC11263395

What OpenQuestion 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 OpenQuestion graph.