Literature DB >> 31515670

Peripheral changes in immune cell populations and soluble mediators after anti-PD-1 therapy in non-small cell lung cancer and renal cell carcinoma patients.

Estefanía Paula Juliá1, Pablo Mandó1,2, Manglio Miguel Rizzo2, Gerardo Rubén Cueto3, Florencia Tsou4, Romina Luca2, Carmen Pupareli4, Alicia Inés Bravo5, Walter Astorino4, José Mordoh1,4,6, Claudio Martín4, Estrella Mariel Levy7.   

Abstract

Patients with non-small cell lung cancer (NSCLC) and renal cell carcinoma (RCC) have shown benefit from anti-PD-1 therapies. However, not all patients experience tumor shrinkage, durable responses or prolonged survival, demonstrating the need to find response markers. In blood samples from NSCLC and RCC patients obtained before and after anti-PD-1 treatment, we studied leukocytes by complete blood cell count, lymphocyte subsets using flow cytometry and plasma concentration of nine soluble mediators, in order to find predictive biomarkers of response and to study changes produced after anti-PD-1 therapy. In baseline samples, discriminant analysis revealed a combination of four variables that helped differentiate stable disease-response (SD-R) from progressive disease (PD) patients: augmented frequency of central memory CD4+ T cells and leukocyte count was associated with response while increased percentage of PD-L1+ natural killer cells and naïve CD4+ T cells was associated with lack of response. After therapy, differential changes between responders and non-responders were found in leukocytes, T cells and TIM-3+ T cells. Patients with progressive disease showed an increase in the frequency of TIM-3 expressing CD4+ and CD8+ T cells, whereas SD-R patients showed a decrease in these subsets. Our findings indicate that a combination of immune variables from peripheral blood (PB) could be useful to distinguish response groups in NSCLC and RCC patients treated with anti-PD-1 therapy. Frequency of TIM-3+ T cells showed differential changes after treatment in PD vs SD-R patients, suggesting that it may be an interesting marker for monitoring progression during therapy.

Entities:  

Keywords:  Anti-PD-1 therapy; NSCLC; Nivolumab; Pembrolizumab; Renal cell carcinoma; TIM-3

Mesh:

Substances:

Year:  2019        PMID: 31515670     DOI: 10.1007/s00262-019-02391-z

Source DB:  PubMed          Journal:  Cancer Immunol Immunother        ISSN: 0340-7004            Impact factor:   6.968


  18 in total

1.  Programmed cell death protein 1 on natural killer cells: fact or fiction?

Authors:  Monica M Cho; Aicha E Quamine; Mallery R Olsen; Christian M Capitini
Journal:  J Clin Invest       Date:  2020-06-01       Impact factor: 14.808

2.  Peripheral CD4+ T cell signatures in predicting the responses to anti-PD-1/PD-L1 monotherapy for Chinese advanced non-small cell lung cancer.

Authors:  Liliang Xia; Hui Wang; Mingjiao Sun; Yi Yang; Chengcheng Yao; Sheng He; Huangqi Duan; Weimin Xia; Ruiming Sun; Yaxian Yao; Zhiwei Chen; Qiong Zhao; Hong Li; Shun Lu; Ying Wang
Journal:  Sci China Life Sci       Date:  2021-01-29       Impact factor: 6.038

Review 3.  Malignant Pleural Effusions-A Window Into Local Anti-Tumor T Cell Immunity?

Authors:  Nicola Principe; Joel Kidman; Richard A Lake; Willem Joost Lesterhuis; Anna K Nowak; Alison M McDonnell; Jonathan Chee
Journal:  Front Oncol       Date:  2021-04-27       Impact factor: 6.244

Review 4.  NK Cell-Based Immunotherapy in Renal Cell Carcinoma.

Authors:  Iñigo Terrén; Ane Orrantia; Idoia Mikelez-Alonso; Joana Vitallé; Olatz Zenarruzabeitia; Francisco Borrego
Journal:  Cancers (Basel)       Date:  2020-01-29       Impact factor: 6.639

Review 5.  Resistance to PD-L1/PD-1 Blockade Immunotherapy. A Tumor-Intrinsic or Tumor-Extrinsic Phenomenon?

Authors:  Luisa Chocarro de Erauso; Miren Zuazo; Hugo Arasanz; Ana Bocanegra; Carlos Hernandez; Gonzalo Fernandez; Maria Jesus Garcia-Granda; Ester Blanco; Ruth Vera; Grazyna Kochan; David Escors
Journal:  Front Pharmacol       Date:  2020-04-07       Impact factor: 5.810

6.  Prospective development and validation of a liquid immune profile-based signature (LIPS) to predict response of patients with recurrent/metastatic cancer to immune checkpoint inhibitors.

Authors:  Jian-Guo Zhou; Anna-Jasmina Donaubauer; Udo Gaipl; Markus Hecht; Benjamin Frey; Ina Becker; Sandra Rutzner; Markus Eckstein; Roger Sun; Hu Ma; Philipp Schubert; Claudia Schweizer; Rainer Fietkau; Eric Deutsch
Journal:  J Immunother Cancer       Date:  2021-02       Impact factor: 13.751

Review 7.  Systemic Blood Immune Cell Populations as Biomarkers for the Outcome of Immune Checkpoint Inhibitor Therapies.

Authors:  Carlos Hernandez; Hugo Arasanz; Luisa Chocarro; Ana Bocanegra; Miren Zuazo; Gonzalo Fernandez-Hinojal; Ester Blanco; Ruth Vera; David Escors; Grazyna Kochan
Journal:  Int J Mol Sci       Date:  2020-03-31       Impact factor: 5.923

8.  HHLA2 and PD-L1 co-expression predicts poor prognosis in patients with clear cell renal cell carcinoma.

Authors:  Qiang-Hua Zhou; Kai-Wen Li; Xu Chen; Hai-Xia He; Sheng-Meng Peng; Shi-Rong Peng; Qiong Wang; Ze-An Li; Yi-Ran Tao; Wen-Li Cai; Ran-Yi Liu; Hai Huang
Journal:  J Immunother Cancer       Date:  2020-01       Impact factor: 13.751

Review 9.  Peripheral blood immune cell-based biomarkers in anti-PD-1/PD-L1 therapy.

Authors:  Kyung Hwan Kim; Chang Gon Kim; Eui-Cheol Shin
Journal:  Immune Netw       Date:  2020-02-10       Impact factor: 6.303

10.  Emerging Blood-Based Biomarkers for Predicting Response to Checkpoint Immunotherapy in Non-Small-Cell Lung Cancer.

Authors:  Shumin Li; Chengyan Zhang; Guanchao Pang; Pingli Wang
Journal:  Front Immunol       Date:  2020-10-16       Impact factor: 7.561

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