Targeting the tumor mutanome for personalized vaccination in a TMB low non-small cell lung cancer

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Dokumenter

  • Fulltext

    Forlagets udgivne version, 3,87 MB, PDF-dokument

  • Katy McCann
  • Adrian Von Witzleben
  • Jaya Thomas
  • Chuan Wang
  • Oliver Wood
  • Divya Singh
  • Konstantinos Boukas
  • Kaidre Bendjama
  • Nathalie Silvestre
  • Nielsen, Finn Cilius
  • Gareth Thomas
  • Tilman Sanchez-Elsner
  • Jason Greenbaum
  • Stephen Schoenberger
  • Bjoern Peters
  • Pandurangan Vijayanand
  • Natalia Savelyeva
  • Christian Ottensmeier

Background Cancer is characterized by an accumulation of somatic mutations, of which a significant subset can generate cancer-specific neoepitopes that are recognized by autologous T cells. Such neoepitopes are emerging as important targets for cancer immunotherapy, including personalized cancer vaccination strategies. Methods We used whole-exome and RNA sequencing analysis to identify potential neoantigens for a patient with non-small cell lung cancer. Thereafter, we assessed the autologous T-cell reactivity to the candidate neoantigens using a long peptide approach in a cultured interferon gamma ELISpot and tracked the neoantigen-specific T-cells in the tumor by T-cell receptor (TCR) sequencing. In parallel, identified gene variants were incorporated into a Modified Vaccinia Ankara-based vaccine, which was evaluated in the human leucocyte antigen A∗0201 transgenic mouse model (HHD). Results Sequencing revealed a tumor with a low mutational burden: 2219 sequence variants were identified from the primary tumor, of which 23 were expressed in the transcriptome, involving 18 gene products. We could demonstrate spontaneous T-cell responses to 5/18 (28%) mutated gene variants, and further analysis of the TCR repertoire of neoantigen-specific CD4 + and CD8 + T cells revealed TCR clonotypes that were expanded in both blood and tumor tissue. Following vaccination of HHD mice, de novo T-cell responses were generated to 4/18 (22%) mutated gene variants; T cells reactive against two variants were also evident in the autologous setting. Subsequently, we determined the major histocompatibility complex restriction of the T-cell responses and used in silico prediction tools to determine the likely neoepitopes. Conclusions Our study demonstrates the feasibility of efficiently identifying tumor-specific neoantigens that can be targeted by vaccination in tumors with a low mutational burden, promising successful clinical exploitation, with trials currently underway.

OriginalsprogEngelsk
Artikelnummere003821
TidsskriftJournal for ImmunoTherapy of Cancer
Vol/bind10
Udgave nummer3
Antal sider14
ISSN2051-1426
DOI
StatusUdgivet - 2022

Bibliografisk note

Funding Information:
Contributors KM: study conception, experimental work, data interpretation, paper writing, paper review; AvW: experimental work, data interpretation, paper writing, paper review; JT: bioinformatic evaluation, data interpretation, paper writing, paper review; CW: animal experimental work, data interpretation, paper writing, paper review; OW: experimental work, data interpretation, paper writing, paper review; DS: experimental work, data interpretation, paper review; KBo: experimental work, data interpretation, paper review; KBe: conception of the experimental works, paper review; NSi: vaccine design, paper review; FCN: experimental work, paper review; GT: data interpretation, paper review; TS-E: data interpretation, paper review; JG: bioinformatic evaluation, data interpretation, paper review; SS: data interpretation, paper review; BP: data interpretation, paper review; PV: data interpretation, paper review; NSa: supervised animal work, data interpretation, paper writing, paper review; CHO: conceived, supervised and led the work, data interpretation, paper writing, paper review.Author acting as guarantor, CHO Funding This study was supported by a Cancer Research UK Centres Network Accelerator Award Grant (A21998). CHO is supported by I-CURE. AvW was supported by DFG fellowship (Deutsche Forschungsgemeinschaft, DFG; research fellowship # WI 5255/1-1:1).

Publisher Copyright:
©

ID: 321195795