High-Throughput immunogenetics for precision medicine in cancer

Andreas Agathangelidis, Elisavet Vlachonikola, Frederic Davi, Anton W. Langerak, Anastasia Chatzidimitriou*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)
5 Downloads (Pure)

Abstract

Cancer is characterized by an extremely complex biological background, which hinders personalized therapeutic interventions. Precision medicine promises to overcome this obstacle through integrating information from different ‘subsystems’, including the host, the external environment, the tumor itself and the tumor micro-environment. Immunogenetics is an essential tool that allows dissecting both lymphoid cancer ontogeny at both a cell-intrinsic and a cell-extrinsic level, i.e. through characterizing micro-environmental interactions, with a view to precision medicine. This is particularly thanks to the introduction of powerful, high-throughput approaches i.e. next generation sequencing, which allow the comprehensive characterization of immune repertoires. Indeed, NGS immunogenetic analysis (Immune-seq) has emerged as key to both understanding cancer pathogenesis and improving the accuracy of clinical decision making in oncology. Immune-seq has applications in lymphoid malignancies, assisting in the diagnosis e.g. through differentiating from reactive conditions, as well as in disease monitoring through accurate assessment of minimal residual disease. Moreover, Immune-seq facilitates the study of T cell receptor clonal dynamics in critical clinical contexts, including transplantation as well as innovative immunotherapy for solid cancers. The clinical utility of Immune-seq represents the focus of the present contribution, where we highlight what can be achieved but also what must be addressed in order to maximally realize the promise of Immune-seq in precision medicine in cancer.

Original languageEnglish
Pages (from-to)80-88
Number of pages9
JournalSeminars in Cancer Biology
Volume84
DOIs
Publication statusAccepted/In press - 30 Oct 2021

Bibliographical note

Funding Information:
This work was supported in part by the Hellenic Foundation for Research and Innovation (HFRI) and the General Secretariat for Research and Innovation (GSRI) of Greece, under grant agreement No 336 (Project CLLon); the project ODYSSEAS (Intelligent and Automated Systems for enabling the Design, Simulation and Development of Integrated Processes and Products) implemented under the “Action for the Strategic Development on the Research and Technological Sector”, funded by the Operational Programme “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014–2020) and co-financed by Greece and the European Union, with grant agreement no: MIS 5,002,462; TRANSCAN 2/NOVEL funded under JTC 2016 from the European Union's Horizon 2020 research and innovation programme under grant agreement No 643,638; NEoteRIC, funded from the European Union's Horizon 2020 research and innovation programme under grant agreement No 871330, and the Greek Precision Medicine Network (GPMN), supervised by the GSRI.

Funding Information:
This work was supported in part by the Hellenic Foundation for Research and Innovation (HFRI) and the General Secretariat for Research and Innovation (GSRI) of Greece, under grant agreement No 336 (Project CLLon); the project ODYSSEAS (Intelligent and Automated Systems for enabling the Design, Simulation and Development of Integrated Processes and Products) implemented under the “Action for the Strategic Development on the Research and Technological Sector”, funded by the Operational Programme "Competitiveness, Entrepreneurship and Innovation" (NSRF 2014–2020) and co-financed by Greece and the European Union , with grant agreement no: MIS 5,002,462; TRANSCAN 2/NOVEL funded under JTC 2016 from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 643,638; NEoteRIC , funded from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871330, and the Greek Precision Medicine Network (GPMN) , supervised by the GSRI.

Publisher Copyright:
© 2021 The Author(s)

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