Frontiers in Oncology (May 2020)
Measuring Intratumoral Heterogeneity of Immune Repertoires
- Diana Vladimirovna Yuzhakova,
- Lilia N. Volchkova,
- Mikhail Valerievich Pogorelyy,
- Mikhail Valerievich Pogorelyy,
- Ekaterina O. Serebrovskaya,
- Ekaterina O. Serebrovskaya,
- Irina A. Shagina,
- Irina A. Shagina,
- Ekaterina A. Bryushkova,
- Ekaterina A. Bryushkova,
- Tatiana O. Nakonechnaya,
- Tatiana O. Nakonechnaya,
- Tatiana O. Nakonechnaya,
- Anna V. Izosimova,
- Daria S. Zavyalova,
- Maria M. Karabut,
- Mark Izraelson,
- Mark Izraelson,
- Mark Izraelson,
- Igor V. Samoylenko,
- Vladimir E. Zagainov,
- Vladimir E. Zagainov,
- Dmitriy M. Chudakov,
- Dmitriy M. Chudakov,
- Dmitriy M. Chudakov,
- Dmitriy M. Chudakov,
- Dmitriy M. Chudakov,
- Elena V. Zagaynova,
- George Vladimirovich Sharonov,
- George Vladimirovich Sharonov,
- George Vladimirovich Sharonov
Affiliations
- Diana Vladimirovna Yuzhakova
- Laboratory of Genomics of Antitumor Adaptive Immunity, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
- Lilia N. Volchkova
- Laboratory of Genomics of Antitumor Adaptive Immunity, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
- Mikhail Valerievich Pogorelyy
- Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
- Mikhail Valerievich Pogorelyy
- Department of Molecular Technologies, Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
- Ekaterina O. Serebrovskaya
- Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
- Ekaterina O. Serebrovskaya
- Department of Molecular Technologies, Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
- Irina A. Shagina
- Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
- Irina A. Shagina
- Department of Molecular Technologies, Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
- Ekaterina A. Bryushkova
- Department of Molecular Technologies, Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
- Ekaterina A. Bryushkova
- Department of Molecular Biology, Moscow State University, Moscow, Russia
- Tatiana O. Nakonechnaya
- Laboratory of Genomics of Antitumor Adaptive Immunity, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
- Tatiana O. Nakonechnaya
- Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
- Tatiana O. Nakonechnaya
- Department of Molecular Technologies, Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
- Anna V. Izosimova
- Laboratory of Genomics of Antitumor Adaptive Immunity, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
- Daria S. Zavyalova
- Laboratory of Genomics of Antitumor Adaptive Immunity, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
- Maria M. Karabut
- Laboratory of Genomics of Antitumor Adaptive Immunity, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
- Mark Izraelson
- Laboratory of Genomics of Antitumor Adaptive Immunity, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
- Mark Izraelson
- Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
- Mark Izraelson
- Department of Molecular Technologies, Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
- Igor V. Samoylenko
- Oncodermatology Department, N. N. Blokhin Russian Cancer Research Center, Moscow, Russia
- Vladimir E. Zagainov
- Laboratory of Genomics of Antitumor Adaptive Immunity, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
- Vladimir E. Zagainov
- Volga District Medical Centre Under Federal Medical and Biological Agency, Nizhny Novgorod, Russia
- Dmitriy M. Chudakov
- Laboratory of Genomics of Antitumor Adaptive Immunity, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
- Dmitriy M. Chudakov
- Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
- Dmitriy M. Chudakov
- Department of Molecular Technologies, Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
- Dmitriy M. Chudakov
- Adaptive Immunity Group, Central European Institute of Technology, Masaryk University, Brno, Czechia
- Dmitriy M. Chudakov
- MiLaboratory LLC, Skolkovo Innovation Centre, Moscow, Russia
- Elena V. Zagaynova
- Laboratory of Genomics of Antitumor Adaptive Immunity, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
- George Vladimirovich Sharonov
- Laboratory of Genomics of Antitumor Adaptive Immunity, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
- George Vladimirovich Sharonov
- Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
- George Vladimirovich Sharonov
- Department of Molecular Technologies, Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
- DOI
- https://doi.org/10.3389/fonc.2020.00512
- Journal volume & issue
-
Vol. 10
Abstract
There is considerable clinical and fundamental value in measuring the clonal heterogeneity of T and B cell expansions in tumors and tumor-associated lymphoid structures—along with the associated heterogeneity of the tumor neoantigen landscape—but such analyses remain challenging to perform. Here, we propose a straightforward approach to analyze the heterogeneity of immune repertoires between different tissue sections in a quantitative and controlled way, based on a beta-binomial noise model trained on control replicates obtained at the level of single-cell suspensions. This approach allows to identify local clonal expansions with high accuracy. We reveal in situ proliferation of clonal T cells in a mouse model of melanoma, and analyze heterogeneity of immunoglobulin repertoires between sections of a metastatically-infiltrated lymph node in human melanoma and primary human colon tumor. On the latter example, we demonstrate the importance of training the noise model on datasets with depth and content that is comparable to the samples being studied. Altogether, we describe here the crucial basic instrumentarium needed to facilitate proper experimental setup planning in the rapidly evolving field of intratumoral immune repertoires, from the wet lab to bioinformatics analysis.
Keywords
