Literature DB >> 29294043

Clinical response to PD-1 blockade correlates with a sub-fraction of peripheral central memory CD4+ T cells in patients with malignant melanoma.

Yoshiko Takeuchi1,2, Atsushi Tanemura3, Yasuko Tada1, Ichiro Katayama3, Atsushi Kumanogoh2, Hiroyoshi Nishikawa1,4.   

Abstract

Cancer immunotherapy that blocks immune checkpoint molecules, such as PD-1/PD-L1, unleashes dysfunctional antitumor T-cell responses and has durable clinical benefits in various types of cancers. Yet its clinical efficacy is limited to a small proportion of patients, highlighting the need for identifying biomarkers that can predict the clinical response by exploring antitumor responses crucial for tumor regression. Here, we explored comprehensive immune-cell responses associated with clinical benefits using PBMCs from patients with malignant melanoma treated with anti-PD-1 monoclonal antibody. Pre- and post-treatment samples were collected from two different cohorts (discovery set and validation set) and subjected to mass cytometry assays that measured the expression levels of 35 proteins. Screening by high dimensional clustering in the discovery set identified increases in three micro-clusters of CD4+ T cells, a subset of central memory CD4+ T cells harboring the CD27+FAS-CD45RA-CCR7+ phenotype, after treatment in long-term survivors, but not in non-responders. The same increase was also observed in clinical responders in the validation set. We propose that increases in this subset of central memory CD4+ T cells in peripheral blood can be potentially used as a predictor of clinical response to PD-1 blockade therapy in patients with malignant melanoma. © The Japanese Society for Immunology. 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  CyTOF; PD-1 blockade; biomarker; cancer immunotherapy; mass cytometry

Mesh:

Substances:

Year:  2018        PMID: 29294043     DOI: 10.1093/intimm/dxx073

Source DB:  PubMed          Journal:  Int Immunol        ISSN: 0953-8178            Impact factor:   4.823


  40 in total

1.  Immunotyping and Quantification of Melanoma Tumor-Infiltrating Lymphocytes.

Authors:  Max O Meneveau; Zeyad T Sahli; Kevin T Lynch; Ileana S Mauldin; Craig L Slingluff
Journal:  Methods Mol Biol       Date:  2021

2.  Combination of host immune metabolic biomarkers for the PD-1 blockade cancer immunotherapy.

Authors:  Ryusuke Hatae; Kenji Chamoto; Young Hak Kim; Kazuhiro Sonomura; Kei Taneishi; Shuji Kawaguchi; Hironori Yoshida; Hiroaki Ozasa; Yuichi Sakamori; Maryam Akrami; Sidonia Fagarasan; Izuru Masuda; Yasushi Okuno; Fumihiko Matsuda; Toyohiro Hirai; Tasuku Honjo
Journal:  JCI Insight       Date:  2020-01-30

Review 3.  Beyond the message: advantages of snapshot proteomics with single-cell mass cytometry in solid tumors.

Authors:  Akshitkumar M Mistry; Allison R Greenplate; Rebecca A Ihrie; Jonathan M Irish
Journal:  FEBS J       Date:  2019-01-07       Impact factor: 5.542

4.  The tissue-resident marker CD103 on peripheral blood T cells predicts responses to anti-PD-1 therapy in gastric cancer.

Authors:  Yohei Nose; Takuro Saito; Kei Yamamoto; Kotaro Yamashita; Koji Tanaka; Kazuyoshi Yamamoto; Tomoki Makino; Tsuyoshi Takahashi; Atsunari Kawashima; Miya Haruna; Michinari Hirata; Azumi Ueyama; Kota Iwahori; Taroh Satoh; Yukinori Kurokawa; Hidetoshi Eguchi; Yuichiro Doki; Hisashi Wada
Journal:  Cancer Immunol Immunother       Date:  2022-07-01       Impact factor: 6.968

5.  LAG-3xPD-L1 bispecific antibody potentiates antitumor responses of T cells through dendritic cell activation.

Authors:  Eunsil Sung; Minkyung Ko; Ju-Young Won; Yunju Jo; Eunyoung Park; Hyunjoo Kim; Eunji Choi; Ui-Jung Jung; Jaehyoung Jeon; Youngkwang Kim; Hyejin Ahn; Da-Som Choi; Seunghyun Choi; Youngeun Hong; Hyeyoung Park; Hanbyul Lee; Yong-Gyu Son; Kyeongsu Park; Jonghwa Won; Soo Jin Oh; Seonmin Lee; Kyu-Pyo Kim; Changhoon Yoo; Hyun Kyu Song; Hyung-Seung Jin; Jaeho Jung; Yoon Park
Journal:  Mol Ther       Date:  2022-05-06       Impact factor: 12.910

6.  Immune tumor board: integral part in the multidisciplinary management of cancer patients treated with cancer immunotherapy.

Authors:  Heinz Läubli; Stefan Dirnhofer; Alfred Zippelius
Journal:  Virchows Arch       Date:  2018-08-25       Impact factor: 4.064

7.  Durable Suppression of Acquired MEK Inhibitor Resistance in Cancer by Sequestering MEK from ERK and Promoting Antitumor T-cell Immunity.

Authors:  Aayoung Hong; Marco Piva; Sixue Liu; Gatien Moriceau; Roger S Lo; Willy Hugo; Shirley H Lomeli; Vincent Zoete; Christopher E Randolph; Zhentao Yang; Yan Wang; Jordan J Lee; Skylar J Lo; Lu Sun; Agustin Vega-Crespo; Alejandro J Garcia; David B Shackelford; Steven M Dubinett; Philip O Scumpia; Stephanie D Byrum; Alan J Tackett; Timothy R Donahue; Olivier Michielin; Sheri L Holmen; Antoni Ribas
Journal:  Cancer Discov       Date:  2020-12-14       Impact factor: 39.397

8.  Early memory differentiation and cell death resistance in T cells predicts melanoma response to sequential anti-CTLA4 and anti-PD1 immunotherapy.

Authors:  Isaure Vanmeerbeek; Daniel M Borras; Jenny Sprooten; Oliver Bechter; Sabine Tejpar; Abhishek D Garg
Journal:  Genes Immun       Date:  2021-06-02       Impact factor: 2.676

9.  Blocking IL1 Beta Promotes Tumor Regression and Remodeling of the Myeloid Compartment in a Renal Cell Carcinoma Model: Multidimensional Analyses.

Authors:  David H Aggen; Casey R Ager; Aleksandar Z Obradovic; Nivedita Chowdhury; Ali Ghasemzadeh; Wendy Mao; Matthew G Chaimowitz; Zoila A Lopez-Bujanda; Catherine S Spina; Jessica E Hawley; Matthew C Dallos; Cheng Zhang; Vinson Wang; Hu Li; Xinzheng V Guo; Charles G Drake
Journal:  Clin Cancer Res       Date:  2020-11-04       Impact factor: 13.801

Review 10.  Melanoma Immunotherapy: Next-Generation Biomarkers.

Authors:  Sabrina A Hogan; Mitchell P Levesque; Phil F Cheng
Journal:  Front Oncol       Date:  2018-05-29       Impact factor: 6.244

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