Evidence map›Paper›PMID 42686754›Full record

ArticleNature communications2026

Surfaceome CRISPR activation screening uncovers ligands regulating tumor sensitivity to NK cell killing.

Ravi K Dinesh, Xiaotong Wang, Imran A Mohammad, Pari Gunasekaran, Kostas Stiklioraitis, Jeremy R Villafuerte, Anirudh Rao, Rogelio A Hernandez-Lopez, John B Sunwoo, Le Cong

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Ravi K Dinesh *Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA. rdinesh@stanford.edu.ORCID http://orcid.org/0000-0003-0227-2897
Xiaotong Wang *Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
Imran A Mohammad *Department of Otolaryngology-Head and Neck Surgery, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-2288-2887
Pari GunasekaranDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
Kostas StiklioraitisDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
Jeremy R VillafuerteDepartment of Bioengineering, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-4229-1793
Anirudh RaoDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0009-0001-0801-2183
Rogelio A Hernandez-LopezDepartment of Bioengineering, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-3968-4908
John B SunwooDepartment of Otolaryngology-Head and Neck Surgery, Stanford University School of Medicine, Stanford, CA, USA. sunwoo@stanford.edu.ORCID http://orcid.org/0000-0002-8393-4196
Le CongDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA. congle@stanford.edu.ORCID http://orcid.org/0000-0003-4725-8714

Funding

Reprogramming the Tumor-Immune Interface in Oral CancerR35DE030054 · NIDCR · STANFORD UNIVERSITY · PI JOHN B SUNWOO · 2020 to 2026
$6.7M
Recombineering-based no-cleavage gene-editing toolkit for large-scale genome engineering and functional screeningR01GM141627 · NIGMS · STANFORD UNIVERSITY · PI Le Cong · 2021 to 2026
$3.3M
Towards Robust Multiplex Genome Engineering Beyond CRISPR-Cas9R35HG011316 · NHGRI · STANFORD UNIVERSITY · PI CONG, LE · 2020 to 2025
$2.8M
Antigen Density Sensors for Cell EngineeringR35GM155437 · NIGMS · STANFORD UNIVERSITY · PI Rogelio Antonio Hernandez-Lopez · 2024 to 2026
$1.2M
NHGRI NIH HHS R35 HG011316NIDCR NIH HHS R35 DE030054NIGMS NIH HHS R01 GM141627NIGMS NIH HHS R35 GM155437U.S. Department of Health & Human Services | National Institutes of Health (NIH) 1R01GM141627U.S. Department of Health & Human Services | National Institutes of Health (NIH) R35DE030054U.S. Department of Health & Human Services | National Institutes of Health (NIH) R35GM155437U.S. Department of Health & Human Services | National Institutes of Health (NIH) R35HG011316
6 · The paper itself

Abstract

Natural killer (NK) cell-based immunotherapies are promising for cancer treatment due to their ability to eliminate cancer cells independently of antigen presentation and "off-the-shelf" utility. However, molecular determinants governing tumor susceptibility to NK cytotoxicity remain incompletely understood. Here we employ CRISPR activation (CRISPRa) screening to identify cancer cell surface regulators of NK killing. Using a surfaceome-focused library, we screen human and murine cancer cell lines co-cultured with NK cells, identifying known and novel ligands modulating NK cytotoxicity. Screens reveal established factors including CD43 and previously uncharacterized regulators CD44, PDPN, and Siglec-1/CD169. Validation with orthogonal approaches confirm that disruption of these factors alters NK killing susceptibility in vitro and in humanized mouse models. Mechanistically, we find that CD43-mediated NK resistance operates independently of its proposed interaction with Siglec-7, and that targeting CD43 on NK cells or CAR T cells substantially enhances cytotoxic activity against leukemia. These results establish gain-of-function surfaceome screening as a powerful tool for identifying therapeutic targets for NK cell-based immunotherapy.

Indexed as

Cytotoxicity, ImmunologicKiller Cells, NaturalAnimalsCell Line, TumorCoculture TechniquesCRISPR-Cas SystemsFemaleHumansHyaluronan ReceptorsImmunotherapyLeukosialinLigandsMiceSialic Acid Binding Immunoglobulin-like LectinsHyaluronan ReceptorsLeukosialinLigandsSialic Acid Binding Immunoglobulin-like Lectins

Identifiers

PMID42686754
PMCPMC13538616

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.