Journal of Shanghai Jiao Tong University (Medical Science) >

2023 , Vol. 43 >Issue 12: 1520 - 1528

DOI: https://doi.org/10.3969/j.issn.1674-8115.2023.12.006

Basic research

Analysis of tumor-related features of non-small cell lung cancer based on TCR repertoire workflow

  • Zhuoming ZHAO ,
  • Zhenhao LIU ,
  • Manman LU ,
  • Yu ZHANG ,
  • Linfeng XU ,
  • Lu XIE
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  • 1.Department of Food Science and Engineering, College of Food Science & Technology, Shanghai Ocean University, Shanghai 201306, China
    2.Shanghai -MOST Key Laboratory of Health and Disease Genomics & Institute of Geonome and Bioinformatics, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai 200237, China
XIE Lu, E-mail: xielu@sibpt.com.

Received date: 2023-07-20

  Accepted date: 2023-11-14

  Online published: 2024-02-01

Supported by

National Natural Science Foundation of China(31870829)

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Abstract

Objective ·To explore the immune-related characteristics of non-small cell lung cancer (NSCLC), discover potential tumor markers in V-J genes, and lay the foundation for establishing a TCR-antigen recognition prediction model. Methods ·A total of 704 NSCLC samples were collected to establish a comprehensive T-cell receptor (TCR) repertoire analysis workflow. The upstream analysis included steps such as raw data processing, quality control, filtering, TCR sequence identification, and extraction. The downstream analysis included repertoire clone distribution, clone typing, V-J gene sharing, CDR3 distribution characteristics, and clone tracking. The sample clone distribution was analyzed by using indices such as Shannon-Weiner index and Chao1 index. Clone typing was performed based on the number of clone amplifications to explore differences among different types. The degree of V-J gene segment sharing was analyzed, and the sharing of low-frequency clone types was determined through clone amplification weight analysis of V-J genes by using two samples of papillary thyroid carcinoma. Finally, analysis of the distribution characteristics of V genes and high-frequency clone type CDR3, and clone tracking analysis were conducted to monitor changes in tumor immune clone frequencies before and after analysis, aiming to identify potential tumor markers. Results ·① Significant differences were observed in clone distribution and clone typing among different NSCLC tissues, as well as among different ages and genders. ② Specific highly-shared V-J genes were identified in the analysis of V-J gene sharing, and non-normal distribution of high-clone V genes and amino acid high-frequency clone types were found in the CDR3 distribution analysis. ③ In the analysis of high-frequency clone type clone tracking, highly expressed or newly expressed high-frequency clone types were observed in NSCLC, suggesting that these clone types could serve as potential tumor-associated antigens or bind with CDR3 reference sequences of new antigens. ④ It was found that the expression frequency of TRBJ2-5 gene, originally low-expressed, significantly increased, indicating its potential role as a key low-frequency gene in tumor immune response. Conclusion ·The TRAV21 and TRBV6.5 genes show high clone amplification in NSCLC and could serve as potential tumor biomarkers.

Key words： T cell receptor (TCR); TCR repertoire; tumor immunity; non-small cell lung cancer (NSCLC)

Cite this article

Zhuoming ZHAO , Zhenhao LIU , Manman LU , Yu ZHANG , Linfeng XU , Lu XIE . Analysis of tumor-related features of non-small cell lung cancer based on TCR repertoire workflow[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2023 , 43(12) : 1520 -1528 . DOI: 10.3969/j.issn.1674-8115.2023.12.006

References

1 CHO J H. Immunotherapy for non-small-cell lung cancer: current status and future obstacles[J]. Immune Netw, 2017, 17(6): 378-391.
2 YANG T, XIONG Y, ZENG Y, et al. Current status of immunotherapy for non-small cell lung cancer[J]. Front Pharmacol, 2022, 13: 989461.
3 JACKSON L P, TJOA B A, MELLERT H, et al. Development of a TCR beta repertoire assay for profiling liquid biopsies from NSCLC donors[J]. Cancer Drug Resist, 2020, 3(3): 563-571.
4 JOSHI K, MILIGHETTI M, CHAIN B M. Application of T cell receptor (TCR) repertoire analysis for the advancement of cancer immunotherapy[J]. Curr Opin Immunol, 2022, 74: 1-8.
5 MCNEEL D G. TCR diversity: a universal cancer immunotherapy biomarker?[J]. J Immunother Cancer, 2016, 4: 69.
6 MEHTA N M, LI Y, PATEL V, et al. Prediction of peptide and TCR CDR3 loops in formation of class I MHC-peptide-TCR complexes using molecular models with solvation[J]. Methods Mol Biol, 2023, 2673: 273-287.
7 KIDMAN J, PRINCIPE N, WATSON M, et al. Characteristics of TCR repertoire associated with successful immune checkpoint therapy responses[J]. Front Immunol, 2020, 11: 587014.
8 赵静静, 简星星, 王广志, 等. TCR组库及其在肿瘤免疫中的应用前景与挑战[J]. 生命科学, 2021, 33(4): 466-471.
8 ZHAO J J, JIAN X X, WANG G Z, et al. TCR library and its application prospect and challenges in tumor immunity[J]. Chinese Bulletin of Life Sciences, 2021, 33(4): 466-471.
9 BODOR J N, BOUMBER Y, BORGHAEI H. Biomarkers for immune checkpoint inhibition in non-small cell lung cancer (NSCLC)[J]. Cancer, 2020, 126(2): 260-270.
10 ROBERT L, TSOI J, WANG X, et al. CTLA4 blockade broadens the peripheral T-cell receptor repertoire[J]. Clin Cancer Res, 2014, 20(9): 2424-2432.
11 ZHANG Y, LIU Z, WEI W, et al. TCR engineered T cells for solid tumor immunotherapy[J]. Exp Hematol Oncol, 2022, 11(1): 38.
12 GARCíA-PARDO M, GORRIA T, MALENICA I, et al. Vaccine therapy in non-small cell lung cancer[J]. Vaccines, 2022, 10(5): 740.
13 ZHU W, PENG Y B, WANG L, et al. Identification of α-fetoprotein-specific T-cell receptors for hepatocellular carcinoma immunotherapy[J]. Hepatology, 2018, 68(2): 574-589.
14 ZHANG Y, JIAN X, XU L, et al. iTCep: a deep learning framework for identification of T cell epitopes by harnessing fusion features[J]. Front Genet, 2023, 14: 1141535.
15 BOLOTIN D A, POSLAVSKY S, MITROPHANOV I, et al. MiXCR: software for comprehensive adaptive immunity profiling[J]. Nat Methods, 2015, 12(5): 380-381.
16 ZHANG W, DU Y P, SU Z, et al. IMonitor: a robust pipeline for TCR and BCR repertoire analysis[J]. Genetics, 2015, 201(2): 459-472.
17 WU Y, BISWAS D, USAITE I, et al. A local human Vδ1 T cell population is associated with survival in nonsmall-cell lung cancer[J]. Nat Cancer, 2022, 3(6): 696-709.
18 WANG Y, LIU Y, CHEN L, et al. T cell receptor beta-chain profiling of tumor tissue, peripheral blood and regional lymph nodes from patients with papillary thyroid carcinoma[J]. Front Immunol, 2021, 12: 595355.
19 SHANNON C E. The mathematical theory of communication. 1950 [J]. MD Comput, 1997, 14(4): 306-317.
20 CHAO A. Nonparametric estimation of the number of classes in a population[J]. Scand J Statist, 1984, 11: 265-270.
21 PIELOU E C. The measurement of diversity in different types of biological collections[J]. J Theor Biol, 1966, 13: 131-144.
22 PALA L, CONFORTI F. The effect of patient sex on the efficacy and safety of anticancer immunotherapy[J]. Expert Opin Drug Saf, 2021, 20(12): 1535-1544.
23 ZHANG Y, LIU B, ZHAO R, et al. The influence of sex on cardiac physiology and cardiovascular diseases[J]. J Cardiovasc Transl Res, 2020, 13(1): 3-13.
24 TADIRI C P, GISINGER T, KAUTZY-WILLER A, et al. The influence of sex and gender domains on COVID-19 cases and mortality[J]. CMAJ, 2020, 192(36): E1041-E1045.
25 YAN D, YANG J Z, JI Z K, et al. Profiling T cell receptor β-chain in responders after immunization with recombinant hepatitis B vaccine[J]. J Gene Med, 2021, 23(9): e3367.
26 赵静静, 澹小秀, 王广志, 等. 生物信息学方法预测病原体抗原蛋白序列中多肽疫苗候选表位[J]. 生命科学研究, 2021, 25(4): 363-371.
26 ZHAO J J, ZHANG X X, WANG G Z, et al. Bioinformatics method for prediction of peptide vaccine candidate epitopes in pathogen antigenic protein sequences[J]. Life Science Research, 2021, 25(4): 363-371.
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