Methods for determining lymphocyte receptor chain pairs

Patent metadata

Field	Value
Publication number	US-12460318-B2
Application number	US-202217835220-A
Country	US
Kind code	B2
Filing date	Jun 8, 2022
Priority date	May 22, 2014
Publication date	Nov 4, 2025
Grant date	Nov 4, 2025

Abstract

Provided herein are high-throughput sequencing methods to study the diversity and functionality of lymphocyte receptor chains and pairing of the same. Specifically, the methods provided herein are used to identify with confidence one or more lymphocyte receptor chain pairs in a sample, for example one or more functional chain pairs.

First claim

The invention claimed is:

1 . A method for identifying a plurality of T-cell receptor chain pairs in a sample comprising a plurality of T-cells or progeny thereof, wherein each of the T-cell receptor chain pairs is from a single T-cell clone, comprising:
partitioning the sample into a plurality of individual vessels to provide a plurality of sample subpopulations; sequencing nucleic acid clonotypes encoding the T-cell receptor chains in each subpopulation of the plurality of sample subpopulations to determine the identity of the T-cell receptor chains in each sample subpopulation; determining the observed distribution of each of the T-cell receptor chains across the sample subpopulations and calculating statistical probabilities that the observed distributions of T-cell receptor chain pairs in the sample subpopulations are independent from one another; identifying the plurality of T-cell receptor chain pairs based on the calculated statistical probabilities.

2 . The method of claim 1 , comprising subjecting the sample to conditions suitable for expansion of one or more of the T-cells to form an expanded sample prior to partitioning the sample.

3 . The method of claim 1 , comprising subjecting one or more of the plurality of sample subpopulations to conditions suitable for expansion of one or more of the T-cells or progeny thereof in the one or more of the sample subpopulations to form one or more expanded sample subpopulations.

4 . The method of claim 1 , further comprising attaching a unique DNA barcode sequence to the T-cell receptor nucleic acid in each sample subpopulation prior to sequencing, wherein the unique DNA barcode sequence identifies the sample subpopulation from which the T-cell receptor nucleic acid originated.

5 . The method of claim 1 , wherein the nucleic acid is cDNA derived from mRNA expressed by the T-cells in each sample subpopulation.

6 . The method of claim 5 , further comprising performing a first strand cDNA reaction on the mRNA expressed by the T-cells.

7 . The method of claim 6 , wherein the first strand cDNA synthesis reaction is specific for T-cell receptor chain mRNA.

8 . The method of claim 6 , wherein the first strand cDNA synthesis is performed with an oligo dT primer.

9 . The method of claim 7 , wherein at the first strand cDNA synthesis comprises first strand cDNA synthesis of the variable regions of the T-cell receptor chain mRNA.

10 . The method of claim 1 , wherein identifying the plurality of T-cell receptor chain pairs comprises identifying one or more T-cell receptor chain pairs that is expressed by a T-cell or progenitor clone present at a frequency of about 1 cell to about 50 cells in the sample.

11 . The method of claim 1 , wherein subjecting the sample to conditions suitable for expansion comprises cell culture of the plurality of T-cells or progeny thereof and polyclonal activation.

12 . The method of claim 1 , wherein subjecting the sample to conditions suitable for expansion comprises cell culture of the plurality of T-cells or progeny thereof and antigen-specific activation.

13 . The method of claim 11 , wherein subjecting the sample to conditions suitable for expansion comprises treating the sample with Epstein Barr virus, CD40L, one or more Toll-like receptor agonists, phorbol 12-myristate 13-acetate (PMA) in combination with ionomycin or phytohemagglutinin (PHA) activation, irradiated allogeneic peripheral blood mononuclear cells (PBMC) in combination with a soluble anti-CD3 monoclonal antibody, or a combination thereof.

14 . The method of claim 11 , wherein subjecting the sample to conditions suitable for expansion comprises treating the sample with one or more cytokines, a cell surface ligand selected from CD40L, BAFF and APRIL, a Toll-like receptor agonist selected from LPS, CpG, R848, PWM, a monoclonal antibody against a cell surface receptor selected from anti-CD40 and anti-IgG, or a feeder cell line providing co-stimulation signals.

15 . The method of claim 1 , wherein calculating the statistical probabilities comprises calculating the statistical probabilities that the observed chain pair occurrences is greater than what would be expected by chance given that the chains of the observed chain pairs do not originate from the same clonal population of T-cells or progenitors thereof.

16 . The method of claim 1 , wherein sequencing the nucleic acid clonotypes comprises sequencing fusion pairs of T-cell receptor chains.

17 . The method of claim 16 , wherein the fusion pairs of lymphocyte receptor chains comprise TCR α-α, TCR β-β, TCR γ-γ, TCR δ-δ, TCR α-β, TCR γ-δ, TCR γ-α, TCR γ-β, TCR δ-α, TCR δ-β, or a combination thereof.

18 . The method of claim 16 , wherein the T-cell receptor chain fusion pairs are sequenced in a manner to maintain the fusion information.

19 . The method of claim 16 , further comprising generating a network of T-cell receptor chain fusion pairs and subjecting the network to network analysis to identify (i) clusters of highly-interconnected chains, and (ii) which chains were present in the same individual container.

Assignees

• Univ British Columbia

Inventors

• Hansen Carl Lars Genghis
• Mewis Georgia Elizabeth
• Heyries Kevin Albert
• Vaninsberghe Michael Andrew
• Da Costa Daniel Jay
• Ricicova Marketa

Classifications

• C07K16/00

  Immunoglobulins [IG], e.g. monoclonal or polyclonal antibodies · CPC title

• G16B30/20

  Sequence assembly · CPC title

• G16B30/10

  Sequence alignment; Homology search · CPC title

• G16B40/00

  ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding · CPC title

• G16B30/00

  ICT specially adapted for sequence analysis involving nucleotides or amino acids · CPC title