Research ArticleOriginal Article

Molecular heterogeneity of anti-PD-1/PD-L1 immunotherapy efficacy is correlated with tumor immune microenvironment in East Asian patients with non-small cell lung cancer

Runsen Jin, Chengming Liu, Sufei Zheng, Xinfeng Wang, Xiaoli Feng, Hecheng Li, Nan Sun and Jie He
Cancer Biology & Medicine August 2020, 17 (3) 768-781; DOI: https://doi.org/10.20892/j.issn.2095-3941.2020.0121

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Figures

  • Correlation between the efficacy of anti-PD-1/PD-L1 immunotherapy and classic driver oncogene mutations in non-small cell lung cancer (NSCLC) patients. (A and B) Box plots evaluating objective response rate (A) and durable clinical benefit (progression-free survival > 6 months) (B) of NSCLC patients harboring EGFR mutations, KRAS mutations, and ALK fusions after initiation of PD-1/PD-L1 blockade treatment, in the 2018 MSKCC database. (C) A box plot evaluating the objective response rate of NSCLC patients, using TIDE prediction scores in the GSE31210 database. (D) A waterfall plot of TIDE prediction scores across 226 NSCLC tumors in the GSE31210 database. Red indicates a tumor that responded to therapy. Blue indicates non-responders. Tumors were divided into 4 categories based on the molecular genotype of NSCLC. In each category, we sorted tumors in descending order according to their TIDE prediction scores. *P < 0.05; **P < 0.01; ***P < 0.001. EGFR mut, EGFR mutation; KRAS mut, KRAS mutation; DCB, durable clinical benefit; Non-DCB, no durable clinical benefit.
    Figure 1

    Correlation between the efficacy of anti-PD-1/PD-L1 immunotherapy and classic driver oncogene mutations in non-small cell lung cancer (NSCLC) patients. (A and B) Box plots evaluating objective response rate (A) and durable clinical benefit (progression-free survival > 6 months) (B) of NSCLC patients harboring EGFR mutations, KRAS mutations, and ALK fusions after initiation of PD-1/PD-L1 blockade treatment, in the 2018 MSKCC database. (C) A box plot evaluating the objective response rate of NSCLC patients, using TIDE prediction scores in the GSE31210 database. (D) A waterfall plot of TIDE prediction scores across 226 NSCLC tumors in the GSE31210 database. Red indicates a tumor that responded to therapy. Blue indicates non-responders. Tumors were divided into 4 categories based on the molecular genotype of NSCLC. In each category, we sorted tumors in descending order according to their TIDE prediction scores. *P < 0.05; **P < 0.01; ***P < 0.001. EGFR mut, EGFR mutation; KRAS mut, KRAS mutation; DCB, durable clinical benefit; Non-DCB, no durable clinical benefit.

  • Meta-analysis of the association between PD-L1 expression and EGFR mutation status in non-small cell lung cancer (NSCLC) patients. (A) A forest plot of studies evaluating PD-L1 expression between EGFR wild-type and EGFR mutation patients. Pooled odds ratios of EGFR group analysis were computed using a random-effects model. (B) A forest plot of studies evaluating PD-L1 expression between EGFR Ex19del mutation and EGFR L858R mutation. Pooled odds ratios of EGFR subgroup analyses were computed using a fixed-effects model. CI, confidence interval.
    Figure 2

    Meta-analysis of the association between PD-L1 expression and EGFR mutation status in non-small cell lung cancer (NSCLC) patients. (A) A forest plot of studies evaluating PD-L1 expression between EGFR wild-type and EGFR mutation patients. Pooled odds ratios of EGFR group analysis were computed using a random-effects model. (B) A forest plot of studies evaluating PD-L1 expression between EGFR Ex19del mutation and EGFR L858R mutation. Pooled odds ratios of EGFR subgroup analyses were computed using a fixed-effects model. CI, confidence interval.

  • Meta-analysis of the association between PD-L1 expression and KRAS or ALK mutation status in non-small-cell lung cancer (NSCLC) patients. (A) A forest plot of studies evaluating PD-L1 expression between KRAS wild-type and KRAS mutation patients. Pooled odds ratios of KRAS group analysis were computed using a random-effects model. (B) A forest plot of studies evaluating PD-L1 expression between ALK wild-type and ALK fusion patients. Pooled odds ratios of ALK group analyses were computed using a fixed-effects model. CI, confidence interval.
    Figure 3

    Meta-analysis of the association between PD-L1 expression and KRAS or ALK mutation status in non-small-cell lung cancer (NSCLC) patients. (A) A forest plot of studies evaluating PD-L1 expression between KRAS wild-type and KRAS mutation patients. Pooled odds ratios of KRAS group analysis were computed using a random-effects model. (B) A forest plot of studies evaluating PD-L1 expression between ALK wild-type and ALK fusion patients. Pooled odds ratios of ALK group analyses were computed using a fixed-effects model. CI, confidence interval.

  • Correlation between the tumor microenvironment based on PD-L1 and CD8+ T cell infiltration and classic driver oncogene mutations in non-small-cell lung cancer (NSCLC) patients. (A and B) Immunohistochemical (IHC) analysis of PD-L1 expression (A) and CD8+ T cell infiltration (B) according to molecular genotype of NSCLC in a cohort of 629 resected NSCLC samples. (C and D) IHC analyses of PD-L1 expression (C) and CD8+ T cell infiltration (D) according to EGFR mutation status. (E) Representative IHC images show classifications of tumor microenvironments based on PD-L1 expression and CD8+ T cell infiltration. Scale bar = 200 ?m. (F and G) IHC analysis of the tumor microenvironment based on PD-L1 and CD8+ T cell infiltration according to the molecular genotype of NSCLC (F) and EGFR mutation status (G). PD-L1−/TIL−: PD-L1 TPS < 1% and CD8+ TIL density < 1%; PD-L1+/TIL−: PD-L1 TPS ≥ 1% and CD8+ TIL density < 1%; PD-L1−/TIL+: PD-L1 TPS < 1% and CD8+ TIL density ≥ 1%; PD-L1+/TIL+: PD-L1 TPS ≥ 1% and CD8+ TIL density ≥ 1%. *P < 0.05, **P < 0.01. EGFR mut, EGFR mutation; KRAS mut, KRAS mutation.
    Figure 4

    Correlation between the tumor microenvironment based on PD-L1 and CD8+ T cell infiltration and classic driver oncogene mutations in non-small-cell lung cancer (NSCLC) patients. (A and B) Immunohistochemical (IHC) analysis of PD-L1 expression (A) and CD8+ T cell infiltration (B) according to molecular genotype of NSCLC in a cohort of 629 resected NSCLC samples. (C and D) IHC analyses of PD-L1 expression (C) and CD8+ T cell infiltration (D) according to EGFR mutation status. (E) Representative IHC images show classifications of tumor microenvironments based on PD-L1 expression and CD8+ T cell infiltration. Scale bar = 200 ?m. (F and G) IHC analysis of the tumor microenvironment based on PD-L1 and CD8+ T cell infiltration according to the molecular genotype of NSCLC (F) and EGFR mutation status (G). PD-L1−/TIL−: PD-L1 TPS < 1% and CD8+ TIL density < 1%; PD-L1+/TIL−: PD-L1 TPS ≥ 1% and CD8+ TIL density < 1%; PD-L1−/TIL+: PD-L1 TPS < 1% and CD8+ TIL density ≥ 1%; PD-L1+/TIL+: PD-L1 TPS ≥ 1% and CD8+ TIL density ≥ 1%. *P < 0.05, **P < 0.01. EGFR mut, EGFR mutation; KRAS mut, KRAS mutation.

  • Correlation between infiltrated immune cell composition and classic driver oncogene mutations in non-small cell lung cancer (NSCLC) patients. The size of the bubble represents the numeric value of immune cell fraction. *P < 0.05; **P < 0.01; ***P < 0.001. EGFR mut, EGFR mutation; KRAS mut, KRAS mutation.
    Figure 5

    Correlation between infiltrated immune cell composition and classic driver oncogene mutations in non-small cell lung cancer (NSCLC) patients. The size of the bubble represents the numeric value of immune cell fraction. *P < 0.05; **P < 0.01; ***P < 0.001. EGFR mut, EGFR mutation; KRAS mut, KRAS mutation.

  • Expression of 6 infiltrated immune cells in 4 molecular subgroups of non-small cell lung cancer (NSCLC) patients. (A–F) Scatter plots of the expression of the specific immune cell types, including M2 macrophages (A), neutrophils (B), resting memory CD4+ T cells (C), activated memory CD4+ T cells (D), CD8+ T cells (E), and regulatory T cells (F), among molecular subgroups of NSCLC patients. EGFR mut, EGFR mutation; KRAS mut, KRAS mutation.
    Figure 6

    Expression of 6 infiltrated immune cells in 4 molecular subgroups of non-small cell lung cancer (NSCLC) patients. (A–F) Scatter plots of the expression of the specific immune cell types, including M2 macrophages (A), neutrophils (B), resting memory CD4+ T cells (C), activated memory CD4+ T cells (D), CD8+ T cells (E), and regulatory T cells (F), among molecular subgroups of NSCLC patients. EGFR mut, EGFR mutation; KRAS mut, KRAS mutation.

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