Cytotoxic T cells swarm by homotypic chemokine signalling.


Journal

eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614

Informations de publication

Date de publication:
13 10 2020
Historique:
received: 02 03 2020
accepted: 27 09 2020
pubmed: 14 10 2020
medline: 16 3 2021
entrez: 13 10 2020
Statut: epublish

Résumé

Cytotoxic T lymphocytes (CTLs) are thought to arrive at target sites either via random search or following signals by other leukocytes. Here, we reveal independent emergent behaviour in CTL populations attacking tumour masses. Primary murine CTLs coordinate their migration in a process reminiscent of the swarming observed in neutrophils. CTLs engaging cognate targets accelerate the recruitment of distant T cells through long-range homotypic signalling, in part mediated via the diffusion of chemokines CCL3 and CCL4. Newly arriving CTLs augment the chemotactic signal, further accelerating mass recruitment in a positive feedback loop. Activated effector human T cells and chimeric antigen receptor (CAR) T cells similarly employ intra-population signalling to drive rapid convergence. Thus, CTLs recognising a cognate target can induce a localised mass response by amplifying the direct recruitment of additional T cells independently of other leukocytes. Immune cells known as cytotoxic T lymphocytes, or CTLs for short, move around the body searching for infected or damaged cells that may cause harm. Once these specialised killer cells identify a target, they launch an attack, removing the harmful cell from the body. CTLs can also recognise and eliminate cancer cells, and can be infused into cancer patients as a form of treatment called adoptive cell transfer immunotherapy. Unfortunately, this kind of treatment does not yet work well on solid tumours because the immune cells often do not infiltrate them sufficiently. It is thought that CTLs arrive at their targets either by randomly searching or by following chemicals secreted by other immune cells. However, the methods used to map the movement of these killer cells have made it difficult to determine how populations of CTLs coordinate their behaviour independently of other cells in the immune system. To overcome this barrier, Galeano Niño, Pageon, Tay et al. employed a three-dimensional model known as a tumouroid embedded in a matrix of proteins, which mimics the tissue environment of a real tumour in the laboratory. These models were used to track the movement of CTLs extracted from mice and humans, as well as human T cells engineered to recognise cancer cells. The experiments showed that when a CTL identifies a tumour cell, it releases chemical signals known as chemokines, which attract other CTLs and recruit them to the target site. Further experiments and computer simulations revealed that as the number of CTLs arriving at the target site increases, this amplifies the chemokine signal being secreted, resulting in more and more CTLs being attracted to the tumour. Other human T cells that had been engineered to recognize cancer cells were also found to employ this method of mass recruitment, and collectively ‘swarm’ towards targeted tumours. These findings shed new light on how CTLs work together to attack a target. It is possible that exploiting the mechanism used by CTLs could help improve the efficiency of tumour-targeting immunotherapies. However, further studies are needed to determine whether these findings can be applied to solid tumours in cancer patients.

Autres résumés

Type: plain-language-summary (eng)
Immune cells known as cytotoxic T lymphocytes, or CTLs for short, move around the body searching for infected or damaged cells that may cause harm. Once these specialised killer cells identify a target, they launch an attack, removing the harmful cell from the body. CTLs can also recognise and eliminate cancer cells, and can be infused into cancer patients as a form of treatment called adoptive cell transfer immunotherapy. Unfortunately, this kind of treatment does not yet work well on solid tumours because the immune cells often do not infiltrate them sufficiently. It is thought that CTLs arrive at their targets either by randomly searching or by following chemicals secreted by other immune cells. However, the methods used to map the movement of these killer cells have made it difficult to determine how populations of CTLs coordinate their behaviour independently of other cells in the immune system. To overcome this barrier, Galeano Niño, Pageon, Tay et al. employed a three-dimensional model known as a tumouroid embedded in a matrix of proteins, which mimics the tissue environment of a real tumour in the laboratory. These models were used to track the movement of CTLs extracted from mice and humans, as well as human T cells engineered to recognise cancer cells. The experiments showed that when a CTL identifies a tumour cell, it releases chemical signals known as chemokines, which attract other CTLs and recruit them to the target site. Further experiments and computer simulations revealed that as the number of CTLs arriving at the target site increases, this amplifies the chemokine signal being secreted, resulting in more and more CTLs being attracted to the tumour. Other human T cells that had been engineered to recognize cancer cells were also found to employ this method of mass recruitment, and collectively ‘swarm’ towards targeted tumours. These findings shed new light on how CTLs work together to attack a target. It is possible that exploiting the mechanism used by CTLs could help improve the efficiency of tumour-targeting immunotherapies. However, further studies are needed to determine whether these findings can be applied to solid tumours in cancer patients.

Identifiants

pubmed: 33046212
doi: 10.7554/eLife.56554
pii: 56554
pmc: PMC7669268
doi:
pii:

Substances chimiques

Ccl3 protein, mouse 0
Ccl4 protein, mouse 0
Chemokine CCL3 0
Chemokine CCL4 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : National Health and Medical Research Council
ID : GNT1135687
Pays : International
Organisme : NSERC
ID : RGPIN 50503-10477
Pays : International
Organisme : NSERC
ID : 50503-10476
Pays : International

Informations de copyright

© 2020, Galeano Niño et al.

Déclaration de conflit d'intérêts

JG, SP, ST, FC, DK, JH, JM, JC, MG, LD, KH, SR, JZ, GR, VP, GO, RW, DN, BK, AW, FL, MR, MB No competing interests declared

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Auteurs

Jorge Luis Galeano Niño (JL)

EMBL Australia, Single Molecule Science node, University of New South Wales, Sydney, Australia.
School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, Australia.

Sophie V Pageon (SV)

EMBL Australia, Single Molecule Science node, University of New South Wales, Sydney, Australia.
School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, Australia.

Szun S Tay (SS)

EMBL Australia, Single Molecule Science node, University of New South Wales, Sydney, Australia.
School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, Australia.

Feyza Colakoglu (F)

EMBL Australia, Single Molecule Science node, University of New South Wales, Sydney, Australia.
School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, Australia.

Daryan Kempe (D)

EMBL Australia, Single Molecule Science node, University of New South Wales, Sydney, Australia.
School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, Australia.

Jack Hywood (J)

Sydney Medical School, The University of Sydney, Sydney, Australia.

Jessica K Mazalo (JK)

EMBL Australia, Single Molecule Science node, University of New South Wales, Sydney, Australia.
School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, Australia.

James Cremasco (J)

EMBL Australia, Single Molecule Science node, University of New South Wales, Sydney, Australia.
School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, Australia.

Matt A Govendir (MA)

EMBL Australia, Single Molecule Science node, University of New South Wales, Sydney, Australia.
School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, Australia.

Laura F Dagley (LF)

The Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia.
Department of Medical Biology, University of Melbourne, Melbourne, Australia.

Kenneth Hsu (K)

Children's Cancer Research Unit, The Children's Hospital at Westmead, Sydney, Australia.

Simone Rizzetto (S)

School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, Australia.
The Kirby Institute for Infection and Immunity in Society, UNSW, Sydney, Australia.

Jerzy Zieba (J)

School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, Australia.
Neuroscience Research Australia (NeuRA), Randwick, Australia.

Gregory Rice (G)

Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Canada.

Victoria Prior (V)

Children's Cancer Research Unit, The Children's Hospital at Westmead, Sydney, Australia.
Discipline of Child and Adolescent Health, University of Sydney, Sydney, Australia.

Geraldine M O'Neill (GM)

Children's Cancer Research Unit, The Children's Hospital at Westmead, Sydney, Australia.
Discipline of Child and Adolescent Health, University of Sydney, Sydney, Australia.

Richard J Williams (RJ)

Biofab3D, St. Vincent's Hospital, Melbourne, Australia.
Institute for Innovation in Mental and Physical Health and Clinical Translation (iMPACT), School of Medicine, Deakin University, Victoria, Australia.

David R Nisbet (DR)

Biofab3D, St. Vincent's Hospital, Melbourne, Australia.
Advanced Biomaterials Lab, Research School of Engineering, ANU, Canberra, Australia.

Belinda Kramer (B)

Children's Cancer Research Unit, The Children's Hospital at Westmead, Sydney, Australia.

Andrew I Webb (AI)

The Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia.
Department of Medical Biology, University of Melbourne, Melbourne, Australia.

Fabio Luciani (F)

School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, Australia.
The Kirby Institute for Infection and Immunity in Society, UNSW, Sydney, Australia.

Mark N Read (MN)

School of Computer Science, Westmead Initiative, and Charles Perkins Centre, University of Sydney, Sydney, Australia.

Maté Biro (M)

EMBL Australia, Single Molecule Science node, University of New South Wales, Sydney, Australia.
School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, Australia.

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