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Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade

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Science  25 Mar 2016:
Vol. 351, Issue 6280, pp. 1463-1469
DOI: 10.1126/science.aaf1490
  • Fig. 1 Heterogeneity and prognostic value of neoantigen landscape in primary NSCLC.

    (A) Total putative neoantigen burden in multiregion sequenced NSCLC tumors. Proportion of clonal neoantigens, identified ubiquitously in every tumor region, are shown in blue; shared subclonal neoantigens, identified as shared in multiple tumor regions but not all, are shown in yellow; and private subclonal neoantigens, identified in only one tumor region, are in red. (B) Total putative neoantigen burden in TCGA LUAD tumors. Proportion of neoantigens arising from clonal (blue) or subclonal (red) mutations is shown. (C) Schematic illustrating use of different neoantigen ITH thresholds, with bar plot showing separation into the two groups. Without an ITH threshold, samples are simply grouped according to upper quartile of total neoantigen burden. For each ITH threshold, the upper quartile of clonal neoantigens is used to separate tumors with high and low clonal neoantigen burden, and the neoantigen ITH threshold further groups samples. For example, an ITH threshold = 0 involves grouping tumors with high clonal neoantigen burden and zero neoantigen heterogeneity separately from those with low clonal neoantigen burden or any neoantigen heterogeneity. (D) Overall survival curves for samples by using different ITH thresholds. Shown are without an ITH threshold [log-rank, P = 0.025, HR = 0.47 (0.24–0.92)]; ITH threshold = 0 [log-rank, P = 0.019, HR = 0.21 (0.051–0.88)]; ITH threshold = 0.01 [log-rank, P = 0.0096, HR = 0.33 (0.14–0.79)]; and ITH threshold = 0.05 [log-rank, P = 0.021, HR = 0.45 (0.22–0.90)]. The number of patients in each group is listed below the survival curves.

  • Fig. 2 Prediction and identification of neoantigen-reactive T cells in NSCLC samples.

    (A) Putative neoantigens predicted for all missense mutations in L011. The MTFR2D326Y neoantigen (FAFQEYDSF) is highlighted. (B) Putative neoantigens predicted for all missense mutations in L012. The CHTF18L769V neoantigen (LLLDIVAPK) and MYADMR30W neoantigen (SPMIVGSPW) are indicated. (C) Evolutionary trees for L011 and L012 based on predicted neoantigens. (D and E) MHC-multimer screening of expanded, region-specific, tumor-infiltrating CD8+ T lymphocytes and healthy donor (HD) CD8+ PBMC controls with candidate neoantigens (L011, n = 288; L012, n = 354) and control HLA-matched viral peptides (L011, n = 10; L012, n = 9). Frequency of CD8+ MHC-multimer–positive cells out of total CD3+CD8+ tumor-infiltrating lymphocyte (TILs) is displayed for (D) and (E), with size of symbol increasing with frequency.

  • Fig. 3 Identification and characterization of tumor-infiltrating neoantigen-reactive CD8+ T cells in early-stage NSCLC.

    (A) MHC-multimer analysis of nonexpanded, tumor-infiltrating CD8+ T lymphocytes isolated from tumor regions 1 to 3 and normal lung tissue of patient L011 identifies CD8+ TILs reactive to mutant MTFR2 peptide. (B) MHC-multimer analysis of nonexpanded, tumor-infiltrating CD8+ T lymphocytes isolated from tumor regions 1 to 3 and normal lung tissue of patient L012 identifies two distinct populations of CD8+ TILs reactive to mutant CHTF18 and MYADM peptide. The frequency of CD8+ MHC-multimer–positive cells out of total CD3+CD8+ TILs is displayed for (A) and (B). (C) Multiparametric flow cytometric analysis of tumor-infiltrating T lymphocyte subsets isolated from L011 region 3. Phenotypic data are representative of all tumor regions. Relative expression of iCTLA-4 (intracellular CTLA-4), surface PD-1, and surface LAG-3 by CD4+FoxP3+ (regulatory T cell), CD4+FoxP3 (CD4 helper T cell), CD8+ multimer–negative, and CD8+ multimer–reactive (CD8+ MTFR2+) T cells is displayed, plotted against iKi67 (intracellular Ki67). (D) Coexpression of PD-1 and iGzmB (intracellular granzyme B) by tumor-infiltrating T lymphocyte subsets isolated from L011 region 3.

  • Fig. 4 Neoantigen clonal architecture and clinical benefit of immune checkpoint blockade.

    (A) Samples are grouped according to clinical benefit, with durable clinical benefit on left and no durable benefit on right [defined as in (2)]. Bar plot depicts clonal neoantigens in blue and subclonal neoantigens in red. Mutational signatures identified within each sample, subtype, and expression of PD-L1 are shown below. (B) Progression-free survival in NSCLC (2) cohort treated with antibody to PD1 either without an ITH threshold [HR = 0.29 (0.12−0.69), log-rank P = 0.0032] or with an ITH threshold of 0.01 [HR = 0.20 (0.07−0.60), log-rank P = 0.0017], 0.02 [HR = 0.25 (0.09−0.67), log-rank P = 0.0034], or 0.05 [HR = 0.17 (0.07−0.44), log-rank P = 0.000061]. (C) Overall survival in melanoma (4) cohort treated with antibody to CTLA-4 either without an ITH threshold [HR = 0.51 (0.23–1.11), P = 0.083] or with an ITH threshold of 0.01 [HR = 0.29 (0.11−0.77), log-rank P = 0.008], 0.02 [HR = 0.34 (0.14−0.81), log-rank P = 0.011], or 0.05 [HR = 0.51 (0.23–1.11), P = 0.083]. An ITH threshold of 0.05 results in the same survival curve as no ITH threshold because no tumors with a high neoantigen burden exhibit >0.05 neoantigen ITH. (D to F) Clonal architecture of (D) CA9903, (E) CR9306, and (F) CR0095, with mutations yielding neoantigens that elicit a T cell response highlighted. Blue dots represent clonal mutations, with subclonal mutations depicted as red dots. Density plots are shown above.

Supplementary Materials

  • Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade

    Nicholas McGranahan, Andrew J. S. Furness, Rachel Rosenthal, Sofie Ramskov, Rikke Lyngaa, Sunil Kumar Saini, Mariam Jamal-Hanjani, Gareth A. Wilson, Nicolai J. Birkbak, Crispin T. Hiley, Thomas B. K. Watkins, Seema Shafi, Nirupa Murugaesu, Richard Mitter, Ayse U. Akarca, Joseph Linares, Teresa Marafioti, Jake Y. Henry, Eliezer M. Van Allen, Diana Miao, Bastian Schilling, Dirk Schadendorf, Levi A. Garraway, Vladimir Makarov, Naiyer A. Rizvi, Alexandra Snyder, Matthew D. Hellmann, Taha Merghoub, Jedd D. Wolchok, Sachet A. Shukla, Catherine J. Wu, Karl S. Peggs, Timothy A. Chan, Sine R. Hadrup, Sergio A. Quezada, Charles Swanton

    Materials/Methods, Supplementary Text, Tables, Figures, and/or References

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    • Materials and Methods
    • Figs. S1 to S7
    • Tables S1 to S5
    • Full Reference List
    Table S3
    A) Differentially expressed immune genes between LUAD and LUSC tumor samples B) Expression of HLA genes between LUAD and LUSC tumor samples by neoantigen quartile C) Differentially expressed immune genes between LUSC normal and tumor samples
    Table S4
    A) Differentially expressed immune genes between tumors with a high neoantigen burden and low neoantigen ITH and remaining tumors B) Differentially expressed immune genes between tumors with a high clonal neoantigen burden (>upper quartile clonal neoantigens) and low clonal neoantigen burden (<lower quartile clonal neoantigens).
    Table S5
    Detailed clinical characteristics of patients from (2)

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