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Frontiers in Oncology
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Frontiers in Oncology
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Frontiers in Oncology
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Measuring Intratumoral Heterogeneity of Immune Repertoires

Authors: Diana Vladimirovna Yuzhakova; Lilia N. Volchkova; Mikhail Valerievich Pogorelyy; Mikhail Valerievich Pogorelyy; Ekaterina O. Serebrovskaya; Ekaterina O. Serebrovskaya; Irina A. Shagina; +24 Authors

Measuring Intratumoral Heterogeneity of Immune Repertoires

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

TCR repertoire, Oncology, clonal expansions, tumour clonality, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, tumour heterogeneity, RC254-282, immunoglobulin repertoire

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Top 10%
Average
Top 10%
Green
gold
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Cancer Research