Publications by authors named "N Vokes"

Introduction: Despite significant successes, immune checkpoint blockade fails to achieve clinical responses in a significant proportion of patients, predictive markers for responses are imperfect and immune-related adverse events (irAEs) are unpredictable. We used T-cell receptor (TCR) sequencing to systematically analyze prospectively collected patient blood samples from a randomized clinical trial of dual immune checkpoint inhibitor therapy to evaluate changes in the T-cell repertoire and their association with response and irAEs.

Methods: Patients with immunotherapy-naïve metastatic non-small cell lung cancer (NSCLC) were treated with ipilimumab and nivolumab according to trial protocol (LONESTAR, NCT03391869).

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  • Approximately 10% of lung adenocarcinomas (LUAD) have mucinous histology (LUADMuc), which is linked to a lighter/absent smoking history and a higher prevalence of KRAS mutations compared to LUAD without this histology (LUADnon-muc).
  • A study analyzed features and treatment outcomes of LUADMuc and LUADnon-muc patients, revealing LUADMuc patients had less aggressive disease characteristics and a poorer response to current therapies, especially immunotherapy.
  • Overall, LUADMuc showed lower objective response rates, shorter progression-free and overall survival compared to LUADnon-muc, highlighting a need for more effective treatment strategies for this subgroup.
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  • The introduction of immune checkpoint blockade (ICB) has greatly improved treatment outcomes for advanced melanoma, but many patients still become resistant to it due to unclear reasons.
  • Although combining different ICB therapies has been shown to enhance response rates, it also comes with increased toxicity for patients.
  • An analysis of tumor samples from ICB-naïve patients revealed that high genomic heterogeneity and low ploidy can identify those who are intrinsically resistant to aPD-1, leading to a predictive model that may help tailor treatment strategies.
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While immune-checkpoint blockade (ICB) has revolutionized treatment of metastatic melanoma over the last decade, the identification of broadly applicable robust biomarkers has been challenging, driven in large part by the heterogeneity of ICB regimens and patient and tumor characteristics. To disentangle these features, we performed a standardized meta-analysis of eight cohorts of patients treated with anti-PD-1 (n=290), anti-CTLA-4 (n=175), and combination anti-PD-1/anti-CTLA-4 (n=51) with RNA sequencing of pre-treatment tumor and clinical annotations. Stratifying by immune-high vs -low tumors, we found that surprisingly, high immune infiltrate was a biomarker for response to combination ICB, but not anti-PD-1 alone.

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  • Immuno-oncology is revolutionizing cancer treatment, but most patients do not see long-lasting benefits, indicating a need for further advancements in the field.
  • Computational immuno-oncology combines biomedical data science with oncology and immunology to enhance the development of effective immunotherapy treatments from research to clinical application.
  • The review highlights 10 key challenges and opportunities in computational immuno-oncology, stressing the need for strong computational methods and teamwork to adapt to rapid changes in clinical demands and technology.
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