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Enregistrement W3103926827 · doi:10.1136/jitc-2020-sitc2020.0155

155 iPSC-derived NK cells mediate robust anti-tumor activity against glioblastoma

2020· article· en· W3103926827 sur OpenAlexaboutno aff
Jeffrey S. Miller, Frank Cichocki, Jianfang Ning, Ryan Bjordahl, Zachary Davis, Katie Tuininga, Hongbo Wang, Paul Rogers, Moyar Ge, Tom Lee, Bob Valamehr, Clark Chen

Notice bibliographique

RevueRegular and Young Investigator Award Abstracts · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueCAR-T cell therapy research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCytotoxic T cellCancer researchImmunotherapyAdoptive cell transferNK-92CytotoxicityPerforinBiologyImmunologyInterleukin 21Immune systemCD8T cellIn vitro

Résumé

récupéré en direct d'OpenAlex

<h3>Background</h3> Gliomas represent the most common brain tumors within the central nervous system, with glioblastoma being the most aggressive type.<sup>1</sup> Conventional treatment combines several approaches including surgery, chemotherapy, and radiation.<sup>2</sup> However, the prognosis for glioblastoma remains unfavorable, with only 5% of patients surviving more than 5 years post-diagnosis.<sup>3</sup> Thus, new treatment approaches are urgently needed. Natural killer (NK) cells directly lyse malignantly transformed or virally infected cells and secrete inflammatory cytokines that polarize cytotoxic immunity. Allogeneic NK cell adoptive transfer has shown clinical benefit in patients with advanced cancer.<sup>4–7</sup> However, limitations of this approach include relatively low numbers of donor NK cells that can be isolated during an apheresis and variability in the quality of NK cells between donors. To overcome these limitations, we have developed a GMP manufacturing strategy to mass produce NK cells from induced pluripotent stem cells (iPSCs) as an approach to off-the-shelf cancer immunotherapy. We refer to these cells as ‘iNK’ (iPSC-derived NK) cells. Here, we provide preclinical data demonstrating the efficacy of iNK cells for immunotherapy against glioblastoma. <h3>Methods</h3> We generated iNK cells using previously published methods.<sup>8–10</sup> iNK cells were used as effectors against an array of patient-derived glioblastoma lines in 2-dimensional live imaging IncuCyte assays where iNK cell-mediated killing was observed over the course of 48 hours. To investigate iNK cell infiltration and cytotoxicity in a more physiological context that accounts for the 3-dimensional architecture of the tumor, we also performed live imaging IncuCyte assays using iNK cells as effectors against glioblastoma spheroids. To test the anti-tumor function of iNK cells in vivo, we implanted patient-derived glioblastoma cells into mice via intracranial injection. Seven days later, 5 mice received intratumoral injections of iNK cells, and 5 mice received vehicle alone (as a control; figure 1A). All mice were monitored for weight and survival over 100 days. Results iNK cells exhibited strong and sustained cytotoxicity against 6 primary patient-derived mesenchymal glioblastoma lines in 2-dimensional IncuCyte assays and complete infiltration and destruction of glioblastoma spheroids in 3-dimensional IncuCyte assays. In xenogeneic adoptive transfer experiments, all mice receiving intratumoral injections of iNK cells survived out to day 100, while all mice in the vehicle group became moribund and had to be sacrificed by day 60 (figure 1B). <h3>Conclusions</h3> iNK cells are highly cytotoxic against glioblastoma cells, and our preclinical in vivo data provides proof-of-concept for future clinical trials. <h3>Ethics Approval</h3> This project has been approved by the University of Minnesota IACUC. Approval ID: 1812-36595A <h3>References</h3> Louis D N, Perry A, Reifenberger G, von Deimling A, Figarella-Branger D, Cavenee W K, Ohgaki H, Wiestler O D, Kleihues P, Ellison D W. The 2016 world health organization classification of tumors of the central nervous system: a summary. <i>Acta Neuropathol</i> 2016;<b>131</b>:803–820. Stupp R, Mason W P, van den Bent M J, Weller M, Fisher B, Taphoorn M J B, Belanger K, Brandes A A, Marosi C, Bogdahn U, Curschmann J, Janzer R C, Ludwin S K, Gorlia T, Allgeier A, Lacombe D, Cairncross J G, Eisenhauer E, Mirimanoff R O, European Organization for Research and Treatment of Cancer Brain Tumor and Radiotherapy Groups; National Cancer Institute of Canada Clinical Trials Group. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. <i>N Engl J Med</i> 2005;<b>352</b>:987–996. Thakkar JP, Dolecek TA, Horbinski C, Ostrom QT, Lightner DD, Barnholz-Sloan JS, Villano JL. Epidemiologic and molecular prognostic review of glioblastoma. <i>Cancer Epidemiol Biomarkers Prev</i> 2017;<b>23</b>:1985–1996. Miller J S, Soignier Y, Panoskaltsis-Mortari A, McNearney S A, Yun G H, Fautsch S K, McKenna D, Le C, Defor T E, Burns L J, Orchard P J, Blazar B R, Wagner J E, Slungaard A, Weisdorf D J, Okazaki J, McGlave P B. Successful adoptive transfer and in vivo expansion of human haploidentical NK cells in patients with cancer. <i>Blood</i> 2005;<b>105</b>:3051–3057. Bachanova V, Cooley S, Defor T E, Verneris M R, Zhang B, McKenna D H, Curtsinger J, Panoskaltsis-Mortari A, Lewis D, Hippen K, McGlave P, Weisdorf D J, Blazar B R, Miller J S. Clearance of acute myeloid leukemia by haploidentical natural killer cells is improved using IL-2 diphtheria toxin fusion protein. <i>Blood</i> 2014;<b>123</b>:3855. Ciurea S O, Schafer J R, Bassett R, Denman C J, Cao K, Willis D, Rondon G, Chen J, Soebbing D, Kaur I, Gulbis A, Ahmed S, Rezvani K, Scpall E J, Lee D A, Champlin R E. Phase 1 clinical trial using mbIL21 ex vivo-expanded donor-derived NK cells after haploidentical transplant. <i>Blood</i> 2017;<b>130</b>:1857–1868. Romee R, Rosario M, Berrien-Elliott M M, Wagner J A, Jewell B A, Schappe T, Leong J W, Abdel-Latif S, Schneider S E, Willey S, Neal C C, Yu L, Oh T, Lee S, Mulder A, Cooper M A, Fehniger T A. Cytokine-induced memory-like natural killer cells exhibit enhanced responses against myeloid leukiemia. <i>Sci Transl Med</i><b>2016</b>:8;375ra123. Valamehr B, Abujarour R, Robinson M, Le T, Robbins D, Shoemaker D, Flynn P. A novel platform to enable the high-throughput derivation and characterization of feeder-free human iPSCs. <i>Sci Rep</i><b>2012</b>:2;213. Valamehr B, Robinson M, Abujarour R, Rezner B, Vranceanu F, Le T, Medcalf A, Lee T T, Fitch M, Robbins D, Flynn P. Platform for induction and maintenance of transgene-free hiPSCs resembling ground state pluripotent stem cells. <i>Stem Cell Reports</i> 2014;<b>2</b>:366–381. Zhu H, Blum R H, Bjordahl R, Gaidarova S, Rogers P, Lee T T, Abujarour R, Bonello G B, Wu J, Tsai P-F, Miller J S, Walcheck B, Valamehr B, Kaufman D S. Pluripotent stem cell-derived NK cells with high-affinity noncleavable CD16a mediate improved antitumor immunity. <i>Blood</i> 2020;<b>135</b>:399–410.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,041
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,031
Tête enseignante GPT0,256
Écart entre enseignants0,225 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2020
Routes d'admission1
Résumé présentoui

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