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Natural Killer (NK) Cells

Overview of attention for book
Natural Killer (NK) Cells
Springer US
Attention for Chapter: CRISPR Screen to Identify Factors that Render Tumor Cells Sensitive or Resistant to Killing by NK Cells
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  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

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Chapter title
CRISPR Screen to Identify Factors that Render Tumor Cells Sensitive or Resistant to Killing by NK Cells
Book title
Natural Killer (NK) Cells
Published in
Methods in molecular biology, January 2022
DOI 10.1007/978-1-0716-2160-8_19
Pubmed ID
Book ISBNs
978-1-07-162159-2, 978-1-07-162160-8
Authors

Zhuang, Xiaoxuan, Long, Eric O, Long, Eric O., Xiaoxuan Zhuang, Eric O. Long

Abstract

Natural killer (NK) cells are an important component of the cancer immune surveillance system. They are regulated by germline-encoded receptors that activate and inhibit their effector function, such as secretion of cytokines and direct lysis of tumor cells and virus-infected cells. Without the need to be primed by prior exposure to tumor antigen, NK cells can detect ligands expressed on tumor cells and selectively kill these cells. NK cells are under strict control by inhibitory receptors that bind to HLA class I on target cells and block early activation signals, thus preventing lysis of target cells. The sensitivity to lysis by NK cells is therefore determined to a large extent by the expression of HLA class I molecules on tumor cells. In addition to receptor-ligand interactions that occur at NK-target cell synapses, many other factors determine the sensitivity of tumor cells to lysis by NK. Intrinsic properties of tumor cells, such as their metabolism and signaling networks establish a threshold above which they will succumb to the death pathways triggered by NK cell attack. Here we provide a protocol for a genome-wide CRISPR screen in tumor cells to identify factors that regulate their sensitivity to primary human NK cells. Tumor cells first transduced for expression of Cas9 are then transduced with a guide RNA (gRNA) library and co-cultured with NK cells. Deep sequencing of the library generated from the genome of tumor cells that survived the selection by NK cells and analysis of the distribution of guide RNAs is performed to identify genes that promote either sensitivity or resistance to NK-mediated killing. The contribution of individual genes to tumor sensitivity can be validated by knockouts using individual gRNAs. The techniques and workflow described here could be applied to primary tumors from cancer patients and reveal tumor-specific points of vulnerability that could be exploited for cancer immunotherapy, such as checkpoint blockade or expression of chimeric antigen receptors specifically designed to activate NK cell cytotoxicity.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 25%
Student > Ph. D. Student 1 25%
Unknown 2 50%
Readers by discipline Count As %
Unspecified 1 25%
Biochemistry, Genetics and Molecular Biology 1 25%
Unknown 2 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 April 2022.
All research outputs
#14,382,632
of 23,479,361 outputs
Outputs from Methods in molecular biology
#4,030
of 13,156 outputs
Outputs of similar age
#236,475
of 510,021 outputs
Outputs of similar age from Methods in molecular biology
#175
of 791 outputs
Altmetric has tracked 23,479,361 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,156 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 67% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 510,021 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.
We're also able to compare this research output to 791 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.