Genomic correlates of response to CTLA-4 blockade in metastatic melanoma

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Science  09 Oct 2015:
Vol. 350, Issue 6257, pp. 207-211
DOI: 10.1126/science.aad0095
  • Fig. 1 Study design and clinical stratification.

    (A) Patients (n = 150) were identified for whole-exome sequencing of tumor and germline DNA. To be included in the original clinical cohort, patients had to have received ipilimumab monotherapy for metastatic cutaneous melanoma, have pretreatment germline and tumor samples available for sequencing, and have had overall survival for >14 days after initiation of ipilimumab therapy. Of these patients, 110 were eventually included in analysis after exclusions due to inadequate postsequencing quality control (n = 40) (18). Manual review of raw sequencing data was performed to exclude samples with evidence suggesting low purity, high contamination by ContEst (33), or discordant copy number quality control. Of the patients, 62, including 2 who failed DNA quality-control, had FFPE tumor samples available for transcriptome sequencing. After manual review for quality control following RNA sequencing, 42 samples were also analyzed for tumor microenvironment signatures, and 40 with matched WES were analyzed for neoantigen expression (14). (B) Patients were stratified into response groups based on RECIST criteria (21) (CR, complete response; PR, partial response; SD, stable disease; PD, progressive disease; MR, mixed response); duration of overall survival (OS); and duration of progression-free survival (PFS). All two-way comparisons were done comparing patients who achieved clinical benefit with ipilimumab (CR or PR by RECIST criteria or OS >1 year with SD by RECIST criteria) (n = 27) to those with minimal or no benefit from ipilimumab (PD by RECIST criteria or OS <1 year with SD by RECIST criteria) (n = 73). An additional cohort of patients who achieved long-term survival (OS < 2 years) after ipilimumab treatment with early tumor progression (PFS <6 months) were considered separately (n = 10).

  • Fig. 2 Overall mutational load, overall neoantigen load, and expression-based neoantigen analysis as predictors of response to ipilimumab.

    (A) Elevated nonsynonymous mutational load and neoantigen load are associated with response to ipilimumab (P = 0.0076 and 0.027, respectively). An additional 20 points are not shown because of outlying high neoantigen loads in a subset of patients. (B) No trend in increased significance was observed when comparing the burden of higher-affinity neoantigens with respect to response to ipilimumab. Lower median inhibitory concentrations imply stronger HLA binding affinity on the x axis (P = 0.027 for affinity <500 nM; P = 0.034 for affinity <250 nM; P = 0.038 for affinity <100 nM; P = 0.042 for affinity <50 nM). An additional 34 points are not shown because of outlying high neoantigen loads in a subset of patients. (C) A sample size of 40 patients with complete DNA-sequencing, RNA-sequencing, and clinical annotation was insufficient to discern significant differences in neoantigen load or expressed neoantigen load among response cohorts, but a trend was observed for increased neoantigen load among patients with clinical benefit compared with those with no clinical benefit (P > 0.05 for all). (D) Patient-specific RNA-sequencing provides distinct information on tumor gene expression compared with TCGA melanoma data from a separate patient cohort. Although TCGA and RNA-seq data agree on the expression of the majority of neoantigens (n = 12,316) for 40 patients who had high-quality DNA- and RNA-sequencing data available for neoantigen and gene expression analysis, TCGA expression data overestimate the number of neoantigens expressed by 6320 in this patient cohort, and 166 neoantigens that are expressed by patient tumors would be missed by TCGA filtering alone. Additionally, a large proportion of neoantigens (n = 4349) are expressed at negligible levels in patient tumors. Asterisks (*) indicate P < 0.05.

  • Fig. 3 Immune microenvironment cytolytic and immune activity correlates with response to ipilimumab.

    (A) Patients who achieved clinical benefit from immune checkpoint blockade therapy had significantly higher levels of tumor cytolytic activity than those who had minimal or no benefit from ipilimumab (P = 0.039). (B) Patients who achieved clinical benefit from ipilimumab therapy had significantly higher levels of expression immune checkpoint receptors than those who did not (CTLA-4: P = 0.033, PD-L2: P = 0.041). One point is not shown because of an outlying high CTLA-4 expression value in a nonresponder patient (>50 reads per kilobase per million mapped reads). (C) Response to ipilimumab did not correlate with expression of or mutations in HLA alleles (P > 0.05 for all). Asterisks (*) indicate P < 0.05.

  • Table 1 Recurrent neoantigens identified exclusively in the cohort showing clinical benefit with their associated HLA types.

    Variants were manually reviewed in the Integrated Genomics Viewer (34).


Supplementary Materials

  • Genomic correlates of response to CTLA4 blockade in metastatic melanoma

    Eliezer M. Van Allen, Diana Miao, Bastian Schilling, Sachet A. Shukla, Christian Blank, Lisa Zimmer, Antje Sucker, Uwe Hillen, Marnix H. Geukes Foppen, Simone M. Goldinger, Jochen Utikal, Jessica C. Hassel, Benjamin Weide, Katharina C. Kaehler, Carmen Loquai, Peter Mohr, Ralf Gutzmer, Reinhard Dummer, Stacey Gabriel, Catherine J. Wu, Dirk Schadendorf, Levi A. Garraway

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

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    • Materials and Methods
    • Figs. S1 to S4
    • Table S3
    Table S1
    Mutation list for all patients
    Table S2
    Detailed clinical and genome characteristics of individual patients
    Table S4
    Neoantigen list with HLA type and predicting MHC binding affinity for all patients
    Table S5
    Germline mutations in HLA class I
    Correction (13 November 2015): An independent group of investigators noticed a small number of missing data entries in Table S4 concerning neoantigen binding affinities in one patient (Pat110 in the Report). Correcting the neoantigen calls in this case does not alter the results or conclusions of this investigation. Figure S1 and Tables S1, S2, S3, and S4 in the supplementary materials have been updated to reflect this change.
    The original version is accessible here.
    Correction (13 April 2016): It has come to Science's attention that the version of Table S4 posted on our website from 10 September 2015 through 13 November 2015 was not the final version intended for publication by the authors. Table S4 had undergone substantial revision during the peer-review process, including optimization of the neoantigen calling algorithm. Regrettably, the unrevised version of Table S4, which had been uploaded with the initial paper submission, was inadvertently posted upon publication. An Erratum pertaining to the version of Table S4 intended for publication-and unrelated to this posting error-was published on 13 November 2015. The link to the final, corrected version of Table S4 has been available on Science's website as of 13 November 2015 and can also be found here.

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