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Contribution of systemic and somatic factors to clinical response and resistance to PD-L1 blockade in urothelial cancer: An exploratory multi-omic analysis

PLoS Medicine, ISSN: 1549-1676, Vol: 14, Issue: 5, Page: e1002309
2017
  • 260
    Citations
  • 0
    Usage
  • 289
    Captures
  • 3
    Mentions
  • 12
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    260
    • Citation Indexes
      258
    • Patent Family Citations
      1
      • 1
    • Policy Citations
      1
      • 1
  • Captures
    289
  • Mentions
    3
    • Blog Mentions
      2
      • 2
    • News Mentions
      1
      • 1
  • Social Media
    12
    • Shares, Likes & Comments
      12
      • Facebook
        12

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Fusing WGCNA and Machine Learning for Immune-Related Gene Prognostic Index in Lung Adenocarcinoma: Precision Prognosis, Tumor Microenvironment Profiling, and Biomarker Discovery

Introduction Therapies targeting programmed death 1 (PD1) and its ligand (PD-L1), as well as CTL-associated protein 4 (CTLA-4), referred to ICI, exhibit remarkable survival benefits

Article Description

Background: Inhibition of programmed death-ligand 1 (PD-L1) with atezolizumab can induce durable clinical benefit (DCB) in patients with metastatic urothelial cancers, including complete remissions in patients with chemotherapy refractory disease. Although mutation load and PD-L1 immune cell (IC) staining have been associated with response, they lack sufficient sensitivity and specificity for clinical use. Thus, there is a need to evaluate the peripheral blood immune environment and to conduct detailed analyses of mutation load, predicted neoantigens, and immune cellular infiltration in tumors to enhance our understanding of the biologic underpinnings of response and resistance. Methods and findings: The goals of this study were to (1) evaluate the association of mutation load and predicted neoantigen load with therapeutic benefit and (2) determine whether intratumoral and peripheral blood T cell receptor (TCR) clonality inform clinical outcomes in urothelial carcinoma treated with atezolizumab. We hypothesized that an elevated mutation load in combination with T cell clonal dominance among intratumoral lymphocytes prior to treatment or among peripheral T cells after treatment would be associated with effective tumor control upon treatment with anti-PD-L1 therapy. We performed whole exome sequencing (WES), RNA sequencing (RNA-seq), and T cell receptor sequencing (TCR-seq) of pretreatment tumor samples as well as TCR-seq of matched, serially collected peripheral blood, collected before and after treatment with atezolizumab. These parameters were assessed for correlation with DCB (defined as progression-free survival [PFS] >6 months), PFS, and overall survival (OS), both alone and in the context of clinical and intratumoral parameters known to be predictive of survival in this disease state. Patients with DCB displayed a higher proportion of tumor-infiltrating T lymphocytes (TIL) (n = 24, Mann-Whitney p = 0.047). Pretreatment peripheral blood TCR clonality below the median was associated with improved PFS (n = 29, log-rank p = 0.048) and OS (n = 29, log-rank p = 0.011). Patients with DCB also demonstrated more substantial expansion of tumor-associated TCR clones in the peripheral blood 3 weeks after starting treatment (n = 22, Mann-Whitney p = 0.022). The combination of high pretreatment peripheral blood TCR clonality with elevated PD-L1 IC staining in tumor tissue was strongly associated with poor clinical outcomes (n = 10, hazard ratio (HR) (mean) = 89.88, HR (median) = 23.41, 95% CI [2.43, 506.94], p(HR > 1) = 0.0014). Marked variations in mutation loads were seen with different somatic variant calling methodologies, which, in turn, impacted associations with clinical outcomes. Missense mutation load, predicted neoantigen load, and expressed neoantigen load did not demonstrate significant association with DCB (n = 25, Mann-Whitney p = 0.22, n = 25, Mann-Whitney p = 0.55, and n = 25, Mann-Whitney p = 0.29, respectively). Instead, we found evidence of time-varying effects of somatic mutation load on PFS in this cohort (n = 25, p = 0.044). A limitation of our study is its small sample size (n = 29), a subset of the patients treated on IMvigor 210 (NCT02108652). Given the number of exploratory analyses performed, we intend for these results to be hypothesis-generating. Conclusions: These results demonstrate the complex nature of immune response to checkpoint blockade and the compelling need for greater interrogation and data integration of both host and tumor factors. Incorporating these variables in prospective studies will facilitate identification and treatment of resistant patients.

Bibliographic Details

NCT02108652
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85020087828&origin=inward; http://dx.doi.org/10.1371/journal.pmed.1002309; http://www.ncbi.nlm.nih.gov/pubmed/28552987; https://clinicaltrials.gov/ct2/show/NCT02108652; https://dx.plos.org/10.1371/journal.pmed.1002309.g002; http://dx.doi.org/10.1371/journal.pmed.1002309.g002; https://dx.plos.org/10.1371/journal.pmed.1002309.g001; http://dx.doi.org/10.1371/journal.pmed.1002309.g001; https://dx.plos.org/10.1371/journal.pmed.1002309.g004; http://dx.doi.org/10.1371/journal.pmed.1002309.g004; https://dx.plos.org/10.1371/journal.pmed.1002309.t001; http://dx.doi.org/10.1371/journal.pmed.1002309.t001; https://dx.plos.org/10.1371/journal.pmed.1002309; https://dx.plos.org/10.1371/journal.pmed.1002309.g003; http://dx.doi.org/10.1371/journal.pmed.1002309.g003; https://dx.doi.org/10.1371/journal.pmed.1002309; https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1002309; https://dx.doi.org/10.1371/journal.pmed.1002309.g002; https://journals.plos.org/plosmedicine/article/figure?id=10.1371/journal.pmed.1002309.g002; https://dx.doi.org/10.1371/journal.pmed.1002309.g003; https://journals.plos.org/plosmedicine/article/figure?id=10.1371/journal.pmed.1002309.g003; https://dx.doi.org/10.1371/journal.pmed.1002309.g001; https://journals.plos.org/plosmedicine/article/figure?id=10.1371/journal.pmed.1002309.g001; https://dx.doi.org/10.1371/journal.pmed.1002309.g004; https://journals.plos.org/plosmedicine/article/figure?id=10.1371/journal.pmed.1002309.g004; https://dx.doi.org/10.1371/journal.pmed.1002309.t001; https://journals.plos.org/plosmedicine/article/figure?id=10.1371/journal.pmed.1002309.t001; http://journals.plos.org/plosmedicine/article?id=10.1371%2Fjournal.pmed.1002309; https://journals.plos.org/plosmedicine/article/file?id=10.1371/journal.pmed.1002309&type=printable; http://journals.plos.org/plosmedicine/article/figure?id=10.1371/journal.pmed.1002309.g003; http://dx.plos.org/10.1371/journal.pmed.1002309.g002; http://www.plosone.org/article/metrics/info:doi/10.1371/journal.pmed.1002309; http://journals.plos.org/plosmedicine/article/file?id=10.1371/journal.pmed.1002309&type=printable; http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1002309; http://journals.plos.org/plosmedicine/article/figure?id=10.1371/journal.pmed.1002309.g004; http://journals.plos.org/plosmedicine/article/figure?id=10.1371/journal.pmed.1002309.g001; http://journals.plos.org/plosmedicine/article/figure?id=10.1371/journal.pmed.1002309.t001; http://dx.plos.org/10.1371/journal.pmed.1002309; http://dx.plos.org/10.1371/journal.pmed.1002309.t001; http://dx.plos.org/10.1371/journal.pmed.1002309.g001; http://dx.plos.org/10.1371/journal.pmed.1002309.g003; http://dx.plos.org/10.1371/journal.pmed.1002309.g004; http://journals.plos.org/plosmedicine/article/figure?id=10.1371/journal.pmed.1002309.g002

Alexandra Snyder; Tavi Nathanson; Samuel A. Funt; Arun Ahuja; Jacqueline Buros Novik; Matthew D. Hellmann; Eliza Chang; Bulent Arman Aksoy; Hikmat Al-Ahmadie; Erik Yusko; Marissa Vignali; Sharon Benzeno; Mariel Boyd; Meredith Moran; Gopa Iyer; Harlan S. Robins; Elaine R. Mardis; Taha Merghoub; Jeff Hammerbacher; Jonathan E. Rosenberg; Dean F. Bajorin; John D. Minna

Public Library of Science (PLoS)

Medicine

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