An Economical, Quantitative, and Robust Protocol for High-Throughput T Cell Receptor Sequencing from Tumor or Blood

Imran Uddin1, Kroopa Joshi2, Theres Oakes1

  • 1Division of Infection and Immunity, UCL, London, UK.

Insights

This study presents a cost-effective and accurate method for analyzing T cell receptor repertoires in tumors. This approach enhances the identification of personalized biomarkers for tracking immune responses during cancer therapy.

Area of Science:

  • Immunology
  • Oncology
  • Genomics

Background:

  • The T cell receptor (TCR) repertoire reflects the adaptive immune response within tumors.
  • TCR analysis holds potential for personalized biomarkers in cancer therapy, particularly immunotherapy.
  • Accurate quantification of TCR frequencies is crucial for monitoring treatment efficacy.

Purpose of the Study:

  • To describe a novel, economical, robust, sensitive, and versatile protocol for TCR repertoire amplification, sequencing, and analysis.
  • To enable accurate measurement of TCR frequencies for tracking host responses in cancer patients.

Main Methods:

  • A key step involves ligating a single-stranded oligonucleotide to the 3' end of TCR cDNA.
  • This enables amplification of all TCR rearrangements with a single primer set per locus.
  • Unique molecular identifiers (UMIs) are incorporated to label each starting cDNA molecule for error correction.

Main Results:

  • The UMI-based approach corrects for sequence errors and differential PCR amplification bias.
  • This leads to a more accurate assessment of true TCR frequencies in biological samples.
  • The method was successfully applied to human tumor lysates, tumor-infiltrating lymphocytes, and peripheral blood.

Conclusions:

  • The described protocol provides an accurate and efficient method for TCR repertoire analysis.
  • This technique can be utilized for developing personalized biomarkers in cancer immunotherapy.
  • The versatility of the method supports its application across various sample types from cancer patients.

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