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 mutations PSA PFS (months) Radiographic PFS
(months)Best overall response OS (months) 1 41 15.2 15.2 SD 44.9 4 708 8.2 12.7 SD 42.2 5 24 19.5 20.6 SD 54.3 6 2 5.1* 51.1 SD 51.4 7 13 25.7* 25.1 SD 49.4 9 25 11.2 11.2 SD 42.8 15 104 30.6* 25.0 SD 45.5 20 31 26.2 26.2 SD 38.4 23 25 30.9 26.9 SD 33.0 *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
mutationsPSA PFS (months) Radiographic PFS
(months)Best overall response OS (months) 3 81 0.7 1.7 PD 2.0 10 49 na 2.1 PD 2.6 12 65 3.1 7.3* SD 8.5 13 2 2.2 3.4 PD 5.3 16 58 na 1.4 PD 5.7 19 49 0.6 3.0 PD 4.2 22 273 0.7 0.7 na 0.7 24 39 0.7 2.9 PD 10.3 25 47 0.7 3.0 PD 5.8 27 41 0.7 2.5 PD 3.4 *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.
Pretreatment Posttreatment Patient # # NS
mutationsGenetic
deficiencyCD8 density
(cells/mm2)PD-L1
density
(immune
cells/mm2)PD-L1 % on
tumor cellsIFN-γ high
(RNA-seq)PSMA/PAP
ELISpotNeoantigen
ELISpotFavorable 1 41 No 3063 393 0 Yes Negative Negative 4 708 PSM2 393 14 0 Yes Negative Negative 5 24 No 282 128 0 No Negative Positive 6 2 No 655 na na No na na 7 13 No 606 52 0 No Positive Positive 9 25 No 290 na na Yes Positive Negative 15 104 FANCA 458 123 0 na Positive Negative 20 31 No 454 86 0 Yes Negative Negative 23 25 No 275 24 0 Yes Negative Negative Unfavorable 3 81 No 197 137 0 No Negative Negative 10 49 No 43 4 0 No na na 12 65 No 118 186 0 No Negative Negative 13 2 No 331 96 0 No Negative Negative 16 58 No 387 1242 0 Yes na na 19 49 No 362 71 0 No na na 22 273 BRCA2 136 172 0 Yes na na 24 39 No 42 113 14 No Negative Negative 25 47 No 83 na na No na na 27 49 No na na na No na na
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
Additional Files
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.
Other Supplementary Material for this manuscript includes the following:
- Data file S1 (Microsoft Excel format). Primary data.
- Clinical protocol (.pdf format)
