• Login
    View Item 
    •   Home
    • The Christie Research Publications Repository
    • All Christie Publications
    • View Item
    •   Home
    • The Christie Research Publications Repository
    • All Christie Publications
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of ChristieCommunitiesTitleAuthorsIssue DateSubmit DateSubjectsThis CollectionTitleAuthorsIssue DateSubmit DateSubjects

    My Account

    LoginRegister

    Local Links

    The Christie WebsiteChristie Library and Knowledge Service

    Statistics

    Display statistics

    T-cell infiltration and clonality may identify distinct survival groups in colorectal cancer: Development and validation of a prognostic model based on the cancer genome atlas (TCGA) and clinical proteomic tumor analysis consortium (CPTAC)

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    Name:
    36497365.pdf
    Size:
    2.403Mb
    Format:
    PDF
    Description:
    Identified with Open Access button
    Download
    Authors
    Campana, L. G.
    Mansoor, Was
    Hill, J.
    Macutkiewicz, C.
    Curran, F.
    Donnelly, D.
    Hornung, B.
    Charleston, P.
    Bristow, Robert G
    Lord, G. M.
    Valpione, Sara
    Show allShow less
    Affiliation
    Department of Surgery, Manchester University NHS Foundation Trust, Manchester M13 9WL, UK
    Issue Date
    2022
    
    Metadata
    Show full item record
    Abstract
    Predicting the survival outcomes of patients with colorectal cancer (CRC) remains challenging. We investigated the prognostic significance of the transcriptome and tumour-infiltrating lymphocyte T-cell receptor (TIL/Tc-TCR) repertoire and analysed TIL/Tc-TCR sequences of The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) CRC cohorts. Using a multivariate Cox regression, we tested whether TIL/Tc-TCR repertoire, patient and tumour characteristics (stage, sidedness, total non-synonymous mutations, microsatellite instability (MSI) and transcriptional signatures) correlated with patient overall survival (OS) and designed a prognostic nomogram. A multivariate analysis (C-index = 0.75) showed that only patient age, disease stage, TIL/Tc degree of infiltration and clonality were independent prognostic factors for OS. The cut-offs for patients' allocation to TIL/Tc abundance subgroups were determined using a strategy of maximally selected rank statistics with the OptimalCutpoints R package. These were "high", "low" and "very high" (90 th percentile) TIL/Tc infiltration-stratified OS (median not reached, 67 and 44.3 months; p < 0.001); the results were validated in the CPTAC cohort. TIL/Tc clonality was prognostic (median OS in "high" vs. "low" clonality not reached and 67.3 months; p = 0.041) and independent of TIL/Tc infiltration. Whilst tumour sidedness was not prognostic, the "very highly" infiltrated tumours were prevalent among right-sided CRCs (p = 0.039) and showed distinct immunological features, with lower Th1 signature (p = 0.004), higher PD-L1 expression (p < 0.001) and likely enrichment in highly suppressory IL1R1+ Tregs (FoxP3 and IL1R1 overexpression, p < 0.001). TIL/Tc abundance and clonality are independent prognosticators in CRC and, combined with clinical variables, refine risk stratification. We identified a subset of CRCs with "very high" TIL/Tc infiltration, poor prognosis and distinct genetic and immunologic features, which may benefit from alternative therapeutic approaches. These results need validation in prospective patient cohorts.
    Citation
    Campana LG, Mansoor W, Hill J, Macutkiewicz C, Curran F, Donnelly D, et al. T-Cell Infiltration and Clonality May Identify Distinct Survival Groups in Colorectal Cancer: Development and Validation of a Prognostic Model Based on The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC). Cancers (Basel). 2022 Nov 29;14(23). PubMed PMID: 36497365. Pubmed Central PMCID: PMC9740634. Epub 2022/12/12. eng.
    Journal
    Cancers
    URI
    http://hdl.handle.net/10541/625892
    DOI
    10.3390/cancers14235883
    PubMed ID
    36497365
    Additional Links
    https://dx.doi.org/10.3390/cancers14235883
    Type
    Article
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.3390/cancers14235883
    Scopus Count
    Collections
    All Christie Publications

    entitlement

    Related articles

    • Lymphocytic infiltration in stage II microsatellite stable colorectal tumors: A retrospective prognosis biomarker analysis.
    • Authors: Sanz-Pamplona R, Melas M, Maoz A, Schmit SL, Rennert H, Lejbkowicz F, Greenson JK, Sanjuan X, Lopez-Zambrano M, Alonso MH, Qu C, McDonnell KJ, Idos GE, Vignali M, Emerson R, Fields P, Guinó E, Santos C, Salazar R, Robins HS, Rennert G, Gruber SB, Moreno V
    • Issue date: 2020 Sep
    • Clonality and antigen-specific responses shape the prognostic effects of tumor-infiltrating T cells in ovarian cancer.
    • Authors: Tsuji T, Eng KH, Matsuzaki J, Battaglia S, Szender JB, Miliotto A, Gnjatic S, Bshara W, Morrison CD, Lele S, Emerson RO, Wang J, Liu S, Robins H, Lugade AA, Odunsi K
    • Issue date: 2020 Jul 7
    • Impact of sidedness of colorectal cancer on tumor immunity.
    • Authors: Takasu C, Nishi M, Yoshikawa K, Tokunaga T, Kashihara H, Yoshimoto T, Shimada M
    • Issue date: 2020
    • A radiomics approach to assess tumour-infiltrating CD8 cells and response to anti-PD-1 or anti-PD-L1 immunotherapy: an imaging biomarker, retrospective multicohort study.
    • Authors: Sun R, Limkin EJ, Vakalopoulou M, Dercle L, Champiat S, Han SR, Verlingue L, Brandao D, Lancia A, Ammari S, Hollebecque A, Scoazec JY, Marabelle A, Massard C, Soria JC, Robert C, Paragios N, Deutsch E, Ferté C
    • Issue date: 2018 Sep
    • A nomogram model based on the number of examined lymph nodes-related signature to predict prognosis and guide clinical therapy in gastric cancer.
    • Authors: Li H, Lin D, Yu Z, Li H, Zhao S, Hainisayimu T, Liu L, Wang K
    • Issue date: 2022
    DSpace software (copyright © 2002 - 2023)  DuraSpace
    Quick Guide | Contact Us
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.