Literature DB >> 32320754

HLA-corrected tumor mutation burden and homologous recombination deficiency for the prediction of response to PD-(L)1 blockade in advanced non-small-cell lung cancer patients.

J H Shim1, H S Kim2, H Cha3, S Kim4, T M Kim5, V Anagnostou6, Y-L Choi7, H A Jung2, J-M Sun2, J S Ahn2, M-J Ahn2, K Park2, W-Y Park8, S-H Lee9.   

Abstract

BACKGROUND: Immune checkpoint inhibitors (ICIs) have been shown to be beneficial for some patients with advanced non-small-cell lung cancer (NSCLC). However, the underlying mechanisms mediating the limited response to ICIs remain unclear. PATIENTS AND METHODS: We carried out whole-exome sequencing on 198 advanced NSCLC tumors that had been sampled before anti-programmed cell death 1 (anti-PD-1)/programmed death-ligand 1 (PD-L1) therapy. Detailed clinical characteristics were collected on these patients. We designed a new method to estimate human leukocyte antigen (HLA)-corrected tumor mutation burden (TMB), a modification which considers the loss of heterozygosity of HLA from conventional TMB. We carried out external validation of our findings utilizing 89 NSCLC samples and 110 melanoma samples from two independent cohorts of immunotherapy-treated patients.
RESULTS: Homology-dependent recombination deficiency was identified in 37 patients (18.7%) and was associated with longer progression-free survival (PFS; P = 0.049). Using the HLA-corrected TMB, non-responders to ICIs were identified, despite having a high TMB (top 25%). Ten patients (21.3% of the high TMB group) were reclassified from the high TMB group into the low TMB group. The objective response rate (ORR), PFS, and overall survival (OS) were all lower in these patients compared with those of the high TMB group (ORR: 20% versus 59%, P = 0.0363; PFS: hazard ratio = 2.91, P = 0.007; OS: hazard ratio = 3.43, P = 0.004). Multivariate analyses showed that high HLA-corrected TMB was associated with a significant survival advantage (hazard ratio = 0.44, P = 0.015), whereas high conventional TMB was not associated with a survival advantage (hazard ratio = 0.63, P = 0.118). Applying this approach to the independent cohorts of 89 NSCLC patients and 110 melanoma patients, TMB-based survival prediction was significantly improved.
CONCLUSION: HLA-corrected TMB can reconcile the observed disparity in relationships between TMB and ICI responses, and is of predictive and prognostic value for ICI therapies.
Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  PD-L1; homology-dependent recombination deficiency; human leukocyte antigen; immunotherapy; non-small-cell lung cancer; tumor mutation burden

Year:  2020        PMID: 32320754     DOI: 10.1016/j.annonc.2020.04.004

Source DB:  PubMed          Journal:  Ann Oncol        ISSN: 0923-7534            Impact factor:   32.976


  41 in total

1.  Effect of HLA genotype on intravesical recurrence after bacillus Calmette-Guérin therapy for non-muscle-invasive bladder cancer.

Authors:  Mizuki Kobayashi; Nobuhiro Fujiyama; Tokiyoshi Tanegashima; Shintaro Narita; Yoshiaki Yamamoto; Naohiro Fujimoto; Shohei Ueda; Ario Takeuchi; Kazuyuki Numakura; Tomonori Habuchi; Hideyasu Matsuyama; Masatoshi Eto; Masaki Shiota
Journal:  Cancer Immunol Immunother       Date:  2021-08-11       Impact factor: 6.968

2.  Using DNA sequencing data to quantify T cell fraction and therapy response.

Authors:  Robert Bentham; Kevin Litchfield; Thomas B K Watkins; Emilia L Lim; Rachel Rosenthal; Carlos Martínez-Ruiz; Crispin T Hiley; Maise Al Bakir; Roberto Salgado; David A Moore; Mariam Jamal-Hanjani; Charles Swanton; Nicholas McGranahan
Journal:  Nature       Date:  2021-09-08       Impact factor: 49.962

3.  Comparison of the tumor immune microenvironment and checkpoint blockade biomarkers between stage III and IV non-small cell lung cancer.

Authors:  Yinjie Gao; Michelle M Stein; Matthew Kase; Amy L Cummings; Ramit Bharanikumar; Denise Lau; Edward B Garon; Sandip P Patel
Journal:  Cancer Immunol Immunother       Date:  2022-07-26       Impact factor: 6.630

4.  Eating away T cell responses in lung cancer.

Authors:  Roberto Ferrara; Luca Roz
Journal:  J Exp Med       Date:  2022-10-10       Impact factor: 17.579

5.  Network-based machine learning approach to predict immunotherapy response in cancer patients.

Authors:  JungHo Kong; Doyeon Ha; Juhun Lee; Inhae Kim; Minhyuk Park; Sin-Hyeog Im; Kunyoo Shin; Sanguk Kim
Journal:  Nat Commun       Date:  2022-06-28       Impact factor: 17.694

6.  Integration of tumor extrinsic and intrinsic features associates with immunotherapy response in non-small cell lung cancer.

Authors:  Denise Lau; Sonal Khare; Michelle M Stein; Prerna Jain; Yinjie Gao; Aicha BenTaieb; Tim A Rand; Ameen A Salahudeen; Aly A Khan
Journal:  Nat Commun       Date:  2022-07-13       Impact factor: 17.694

7.  2020 Innovation-Based Optimism for Lung Cancer Outcomes.

Authors:  Erin L Schenk; Tejas Patil; Jose Pacheco; Paul A Bunn
Journal:  Oncologist       Date:  2020-12-20

Review 8.  Regulation of the antigen presentation machinery in cancer and its implication for immune surveillance.

Authors:  Adithya Balasubramanian; Thomas John; Marie-Liesse Asselin-Labat
Journal:  Biochem Soc Trans       Date:  2022-04-29       Impact factor: 4.919

Review 9.  Impact of cancer evolution on immune surveillance and checkpoint inhibitor response.

Authors:  Yin Wu; Dhruva Biswas; Charles Swanton
Journal:  Semin Cancer Biol       Date:  2021-02-22       Impact factor: 17.012

Review 10.  Acquired Resistance to Immune Checkpoint Blockades: The Underlying Mechanisms and Potential Strategies.

Authors:  Binghan Zhou; Yuan Gao; Peng Zhang; Qian Chu
Journal:  Front Immunol       Date:  2021-06-14       Impact factor: 7.561

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