Research ArticleCancer

Neoantigen responses, immune correlates, and favorable outcomes after ipilimumab treatment of patients with prostate cancer

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Science Translational Medicine  01 Apr 2020:
Vol. 12, Issue 537, eaaz3577
DOI: 10.1126/scitranslmed.aaz3577
  • Fig. 1 Clinical trial schema.

    IPI, ipilimumab; WES, whole-exome sequencing; RNA-seq, RNA sequencing.

  • Fig. 2 Clinical outcomes of patients with metastatic prostate cancer treated with ipilimumab.

    (A) Patients were stratified into response cohorts based on composite of radiographic/clinical progression-free survival (rcPFS) and overall survival (OS). PSA PFS for total cohort (top; n = 26) and favorable (n = 9) and unfavorable (n = 8) cohorts (bottom) were estimated by the Kaplan-Meier method. (B) Radiographic PFS for total cohort (top; n = 27) and favorable (n = 9) and unfavorable (n = 10) cohorts (bottom) were estimated by the Kaplan-Meier method. (C) OS for total cohort (top; n = 29) and favorable (n = 9) and unfavorable (n = 10) cohorts (bottom) were estimated by the Kaplan-Meier method. (D) Composite of rcPFS. Each bar represents an individual patient (n = 27). Black arrows denote patients who are having ongoing responses. The favorable cohort is depicted by green bars (n = 9), the unfavorable cohort is depicted by purple bars (n = 10), and the remaining patients are depicted by gray bars (n = 8). (E) The favorable cohort is represented by green closed circles (n = 9), the unfavorable cohort is represented by purple open squares (n = 10), and the remaining patients are represented by gray closed triangles (n = 8). Black dots represent patients who are still alive.

  • Fig. 3 Immune correlatives in pretreatment tissue associated with the favorable versus the unfavorable cohorts.

    (A) IFN-γ response pathway expression signature in the pretreatment prostate tumor tissues obtained from the favorable cohort (n = 8) versus the unfavorable cohort (n = 10) based on GSEA. (B) Intratumoral immune subpopulations in the favorable cohort (n = 8) versus the unfavorable cohort (n = 10) based on RNA-seq analyses. Unpaired t test was used to determine statistical significance. (C) T cell infiltration in the favorable cohort versus the unfavorable cohort based on representative IHC staining in pretreatment tissues. A 20× magnification for the large outer squares and a 40× magnification for the small inner squares were used. Treg, regulatory T cell; TH17, T helper 17 cell; Gr-B, granzyme B.

  • Fig. 4 T cell responses to prostate tumor–associated antigens.

    (A) Pie charts denoting the patients within the favorable cohort with T cell responses against prostate-specific membrane antigen (PSMA) and prostatic acid phosphatase (PAP). (B) Raw ELISpot data and graphical representation of T cell responses against PSMA in patient #7. Unpaired t test was used to determine statistical significance. **P ≤ 0.01. (C) Raw ELISpot data and graphical representation of T cell responses against PAP in patients #7, #9, and #15. Unpaired t test was used to determine statistical significance. *P ≤ 0.05, **P ≤ 0.01, and ****P ≤ 0.0001.

  • Fig. 5 T cell responses to prostate cancer neoantigens.

    (A) T cell responses against protein-l-isoaspartate O-methyltransferase domain–containing protein 2 isoform 1 in patient #5 before and after ipilimumab treatment. The table (top) demonstrates the amino acid change between the wild-type (WT) and mutant sequences. Raw ELISpot data (bottom left) and graphical representation of T cell responses (bottom middle) against the neoantigen are shown. Depletion of CD4 or CD8 T cells in ELISpot assays (bottom right) against the neoantigens is shown. Unpaired t test was used to determine statistical significance. **P ≤ 0.01. ns, not significant. (B) T cell responses against rho guanine nucleotide exchange factor 37 and dihydropyrimidinase in patient #7 before and after ipilimumab treatment. The tables (left) demonstrate the amino acid changes between the wild-type and mutant sequences. Raw ELISpot data (left middle) and graphical representation of T cell responses (right middle) against the neoantigens are shown. Depletion of CD4 or CD8 T cells in ELISpot assays (right) against the neoantigens is shown. Unpaired t test was used to determine statistical significance. *P ≤ 0.05 and ***P ≤ 0.001.

  • Table 1 Clinical outcomes for the favorable cohort.

    Blue font indicates that the patients are having ongoing responses. SD, stable disease. NS, nonsynonymous.

    Patient ## NS mutationsPSA PFS (months)Radiographic PFS
    (months)
    Best overall responseOS (months)
    14115.215.2SD44.9
    47088.212.7SD42.2
    52419.520.6SD54.3
    625.1*51.1SD51.4
    71325.7*25.1SD49.4
    92511.211.2SD42.8
    1510430.6*25.0SD45.5
    203126.226.2SD38.4
    232530.926.9SD33.0

    *The patient started abiraterone acetate before developing PSA progression.

    • Table 2 Clinical outcomes for the unfavorable cohort.

      na, not available. For patients na for PSA PFS, both patients had undetectable serum PSA levels before receiving ipilimumab.

      Patient ## NS
      mutations
      PSA PFS (months)Radiographic PFS
      (months)
      Best overall responseOS (months)
      3810.71.7PD2.0
      1049na2.1PD2.6
      12653.17.3*SD8.5
      1322.23.4PD5.3
      1658na1.4PD5.7
      19490.63.0PD4.2
      222730.70.7na0.7
      24390.72.9PD10.3
      25470.73.0PD5.8
      27410.72.5PD3.4

      *The patient’s clinical PFS was 5.1 months.

      • Table 3 Summary of immune correlatives associated with favorable and unfavorable clinical outcomes.

        na, not available because of insufficient amount of PBMCs.

        PretreatmentPosttreatment
        Patient ## NS
        mutations
        Genetic
        deficiency
        CD8 density
        (cells/mm2)
        PD-L1
        density
        (immune
        cells/mm2)
        PD-L1 % on
        tumor cells
        IFN-γ high
        (RNA-seq)
        PSMA/PAP
        ELISpot
        Neoantigen
        ELISpot
        Favorable141No30633930YesNegativeNegative
        4708PSM2393140YesNegativeNegative
        524No2821280NoNegativePositive
        62No655nanaNonana
        713No606520NoPositivePositive
        925No290nanaYesPositiveNegative
        15104FANCA4581230naPositiveNegative
        2031No454860YesNegativeNegative
        2325No275240YesNegativeNegative
        Unfavorable381No1971370NoNegativeNegative
        1049No4340Nonana
        1265No1181860NoNegativeNegative
        132No331960NoNegativeNegative
        1658No38712420Yesnana
        1949No362710Nonana
        22273BRCA21361720Yesnana
        2439No4211314NoNegativeNegative
        2547No83nanaNonana
        2749NonananaNonana

      Supplementary Materials

      • stm.sciencemag.org/cgi/content/full/12/537/eaaz3577/DC1

        Fig. S1. Representative PD-L1 IHC staining within the prostate tumor microenvironment.

        Fig. S2. Schema on identifying tumor-specific mutations and T cell responses to cancer neoantigens.

        Fig. S3. Number of nonsynonymous mutations in primary and metastatic prostate cancers.

        Fig. S4. Number of predicted neoantigens in primary versus metastatic prostate cancer using NetMHCpan.

        Fig. S5. Number of nonsynonymous mutations in the prostate tumor tissues obtained from the favorable versus unfavorable cohorts.

        Table S1. Baseline characteristics and laboratory values.

        Table S2. Metastatic distribution of the patients at baseline.

        Table S3. Prior systemic therapies.

        Table S4. Selected irAEs.

        Table S5. Identifying potential neoantigens with WES and RNA-seq.

        Table S6. Comparison of identified and predicted neoantigens.

        Data file S1. Primary data.

        Clinical protocol

      • The PDF file includes:

        • Fig. S1. Representative PD-L1 IHC staining within the prostate tumor microenvironment.
        • Fig. S2. Schema on identifying tumor-specific mutations and T cell responses to cancer neoantigens.
        • Fig. S3. Number of nonsynonymous mutations in primary and metastatic prostate cancers.
        • Fig. S4. Number of predicted neoantigens in primary versus metastatic prostate cancer using NetMHCpan.
        • Fig. S5. Number of nonsynonymous mutations in the prostate tumor tissues obtained from the favorable versus unfavorable cohorts.
        • Table S1. Baseline characteristics and laboratory values.
        • Table S2. Metastatic distribution of the patients at baseline.
        • Table S3. Prior systemic therapies.
        • Table S4. Selected irAEs.
        • Table S5. Identifying potential neoantigens with WES and RNA-seq.
        • Table S6. Comparison of identified and predicted neoantigens.

        [Download PDF]

        Other Supplementary Material for this manuscript includes the following:

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