ArticleMolecular therapy. Methods & clinical development2020
Evaluating the Potential of T Cell Receptor Repertoires in Predicting the Prognosis of Resectable Non-Small Cell Lung Cancers.
Article in Molecular therapy. Methods & clinical development, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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26 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.
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- Exploring the potential of the TCR repertoire as a tumor biomarker (Review).Oncology letters · 2024Review
- Effects of different KRAS mutants and Ki67 expression on diagnosis and prognosis in lung adenocarcinoma.Scientific reports · 2024Article
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- TCRpred: incorporating T-cell receptor repertoire for clinical outcome prediction.Frontiers in genetics · 2024Article
- The characteristics of intratumoral microbial community reflect the development of lung adenocarcinoma.Frontiers in microbiology · 2024Article
- The Evaluation of Prognostic Value and Immune Characteristics of Ferroptosis-Related Genes in Lung Squamous Cell Carcinoma.Global medical genetics · 2023Article
- Prognostic biomarkers correlated with immune infiltration in non-small cell lung cancer.FEBS open bio · 2023Article
- Molecular characterization of colorectal adenoma and colorectal cancer via integrated genomic transcriptomic analysis.Frontiers in oncology · 2023Article
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- Bacterial biomarkers capable of identifying recurrence or metastasis carry disease severity information for lung cancer.Frontiers in microbiology · 2022Article
- Discussion of tumor mutation burden as an indicator to predict efficacy of immune checkpoint inhibitors: A case report.Frontiers in oncology · 2022Article
- A Novel Nomogram Model to Predict the Recurrence-Free Survival and Overall Survival of Hepatocellular Carcinoma.Frontiers in oncology · 2022Article
- Lung Cancer Stage Prediction Using Multi-Omics Data.Computational and mathematical methods in medicine · 2022Article
- Predicting Tumor Mutational Burden From Lung Adenocarcinoma Histopathological Images Using Deep Learning.Frontiers in oncology · 2022Article
- A Framework to Predict the Molecular Classification and Prognosis of Breast Cancer Patients and Characterize the Landscape of Immune Cell Infiltration.Computational and mathematical methods in medicine · 2022Article
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Authors and funding
11 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
For resectable cancer patients, a method that could precisely predict the risk of postoperative recurrence would be crucial for guiding adjuvant treatment. Since T cell receptor (TCR) repertoires had been shown to be closely related to the dynamics of cancers, here we enrolled a cohort of patients to evaluate the potential of TCR repertoires in predicting the prognosis of resectable non-small cell lung cancers. Specifically, TCRβ repertoires were analyzed in surgical tumor tissues and matched adjacent non-tumor tissues from 39 patients enrolled with resectable non-small cell lung cancer, through target enrichment and high-throughput sequencing. As a result, there are significant differences between the TCR repertories of tumor samples and those of matched adjacent non-tumor samples as evaluated by criteria like the number of clonotypes. In addition, TCR repertoires were significantly associated with a few clinical features, as well as somatic mutations. Finally, certain TCRβ variable-joining (V-J) pairings were featured to build a logistic regression model in predicting postoperative recurrence of resectable non-small cell lung cancers with a testing area under the receiver operating characteristic curve (AUC) of around 0.9. Thus, we hypothesize that TCR repertoires could be potentially used to predict prognosis after curative surgery for non-small cell lung cancer patients.
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