Literature DB >> 28405516

Assessment of tumor-infiltrating TCRVγ9Vδ2 γδ lymphocyte abundance by deconvolution of human cancers microarrays.

Marie Tosolini1, Frédéric Pont2, Mary Poupot3, François Vergez4, Marie-Laure Nicolau-Travers5, David Vermijlen6, Jean-Emmanuel Sarry7, Francesco Dieli8, Jean-Jacques Fournié3.   

Abstract

Most human blood γδ cells are cytolytic TCRVγ9Vδ2+ lymphocytes with antitumor activity. They are currently investigated in several clinical trials of cancer immunotherapy but so far, their tumor infiltration has not been systematically explored across human cancers. Novel algorithms allowing the deconvolution of bulk tumor transcriptomes to find the relative proportions of infiltrating leucocytes, such as CIBERSORT, should be appropriate for this aim but in practice they fail to accurately recognize γδ T lymphocytes. Here, by implementing machine learning from microarray data, we first improved the computational identification of blood-derived TCRVγ9Vδ2+ γδ lymphocytes and then applied this strategy to assess their abundance as tumor infiltrating lymphocytes (γδ TIL) in ∼10,000 cancer biopsies from 50 types of hematological and solid malignancies. We observed considerable inter-individual variation of TCRVγ9Vδ2+γδ TIL abundance both within each type and across the spectrum of cancers tested. We report their prominence in B cell-acute lymphoblastic leukemia (B-ALL), acute promyelocytic leukemia (M3-AML) and chronic myeloid leukemia (CML) as well as in inflammatory breast, prostate, esophagus, pancreas and lung carcinoma. Across all cancers, the abundance of αβ TILs and TCRVγ9Vδ2+ γδ TILs did not correlate. αβ TIL abundance paralleled the mutational load of tumors and positively correlated with inflammation, infiltration of monocytes, macrophages and dendritic cells (DC), antigen processing and presentation, and cytolytic activity, in line with an association with a favorable outcome. In contrast, the abundance of TCRVγ9Vδ2+ γδ TILs did not correlate with these hallmarks and was variably associated with outcome, suggesting that distinct contexts underlie TCRVγ9Vδ2+ γδ TIL and αβ TIL mobilizations in cancer.

Entities:  

Keywords:  Artificial intelligence; cancer; data mining; deconvolution; gamma delta lymphocyte; machine learning; microarray; transcriptome

Year:  2017        PMID: 28405516      PMCID: PMC5384348          DOI: 10.1080/2162402X.2017.1284723

Source DB:  PubMed          Journal:  Oncoimmunology        ISSN: 2162-4011            Impact factor:   8.110


  52 in total

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Journal:  J Mol Diagn       Date:  2000-02       Impact factor: 5.568

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Journal:  Proc Natl Acad Sci U S A       Date:  2005-09-30       Impact factor: 11.205

6.  Human Vγ9Vδ2 T cells specifically recognize and kill acute myeloid leukemic blasts.

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Journal:  J Immunol       Date:  2012-03-30       Impact factor: 5.422

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8.  The prognostic landscape of genes and infiltrating immune cells across human cancers.

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Journal:  Nat Med       Date:  2015-07-20       Impact factor: 53.440

9.  Effector Vγ9Vδ2 T cells dominate the human fetal γδ T-cell repertoire.

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Journal:  Proc Natl Acad Sci U S A       Date:  2015-01-23       Impact factor: 11.205

10.  Landscape of tumor-infiltrating T cell repertoire of human cancers.

Authors:  Bo Li; Taiwen Li; Jean-Christophe Pignon; Binbin Wang; Jinzeng Wang; Sachet A Shukla; Ruoxu Dou; Qianming Chen; F Stephen Hodi; Toni K Choueiri; Catherine Wu; Nir Hacohen; Sabina Signoretti; Jun S Liu; X Shirley Liu
Journal:  Nat Genet       Date:  2016-05-30       Impact factor: 38.330

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  51 in total

1.  Single-cell RNA sequencing unveils the shared and the distinct cytotoxic hallmarks of human TCRVδ1 and TCRVδ2 γδ T lymphocytes.

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2.  Distinctive features of tumor-infiltrating γδ T lymphocytes in human colorectal cancer.

Authors:  S Meraviglia; E Lo Presti; M Tosolini; C La Mendola; V Orlando; M Todaro; V Catalano; G Stassi; G Cicero; S Vieni; J J Fourniè; F Dieli
Journal:  Oncoimmunology       Date:  2017-07-13       Impact factor: 8.110

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Journal:  Oncoimmunology       Date:  2017-10-04       Impact factor: 8.110

4.  T Cell Reprogramming Against Cancer.

Authors:  Samuel G Katz; Peter M Rabinovich
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Review 5.  Structure-Activity Relationships of Butyrophilin 3 Ligands.

Authors:  Andrew J Wiemer
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6.  Boosting γδ T cell-mediated antibody-dependent cellular cytotoxicity by PD-1 blockade in follicular lymphoma.

Authors:  Cédric Rossi; Pauline Gravelle; Emilie Decaup; Julie Bordenave; Mary Poupot; Marie Tosolini; Don-Marc Franchini; Camille Laurent; Renaud Morin; Jean-Michel Lagarde; Loïc Ysebaert; Laetitia Ligat; Christine Jean; Ariel Savina; Christian Klein; Alba Matas Céspedes; Patricia Perez-Galan; Jean-Jacques Fournié; Christine Bezombes
Journal:  Oncoimmunology       Date:  2018-12-17       Impact factor: 8.110

Review 7.  Gamma Delta T-Cell Based Cancer Immunotherapy: Past-Present-Future.

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Review 8.  Butyrophilin3A proteins and Vγ9Vδ2 T cell activation.

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Journal:  Semin Cell Dev Biol       Date:  2018-03-09       Impact factor: 7.727

Review 9.  γδ T cells: pleiotropic immune effectors with therapeutic potential in cancer.

Authors:  Bruno Silva-Santos; Sofia Mensurado; Seth B Coffelt
Journal:  Nat Rev Cancer       Date:  2019-07       Impact factor: 60.716

Review 10.  Exploring natural killer cell immunology as a therapeutic strategy in lung cancer.

Authors:  Jonas B Hess; Kate D Sutherland; Sarah A Best
Journal:  Transl Lung Cancer Res       Date:  2021-06
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