Pik3ca mutation drives prostate cancer
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Supplementary Material
Supplementary Methods
QRT-PCR: Prostate RNA was isolated using the RNeasy mini purification kit (#74134,
Qiagen), TURBO DNase treated (#AM1907, Ambion by Life Technologies), and reverse
transcribed with the Transcriptor First Strand cDNA Synthesis kit (#04897030001, Roche)
according to manufacturer’s instructions. Amplification of cDNA was performed on a
LightCycler 480 Instrument (Roche) and samples were normalized to Gapdh (1). Fold change
was calculated using the 2–ΔΔCt method. Pbsn and Nkx3.1 mRNA was detected using primers
published previously (2).
Western blotting: Protein lysates (20 g) were loaded onto a 4-12% gradient pre-cast gel
(#NW04122BOX, Thermo Fisher Scientific) in 4x BOLTTM LDS sample buffer (#B0007,
Thermo Fisher Scientific). Using the iBlotTM 2 gel transfer device (#IB21001, Thermo Fisher
Scientific), proteins were transferred to PVDF membrane (#IB24002, Thermo Fisher
Scientific) and blocked in blocking buffer 1 (BB1, Zeptosens) before incubating overnight with
primary antibodies (Supplementary Table 6) diluted 1:1,000 in assay buffer CAB1 (Zeptosens).
Membranes were washed in TBS/T (0.1% Tween 20) and incubated with 1:20,000 IRDye®
800CW goat-anti-rabbit IgG (H+L) secondary antibody (#925-32211, LI-COR Biosciences)
and bands detected using the LI-COR Odyssey CLx infrared imaging system.
Supplementary Table Legends
Supplementary Table 1: PIK3CA mutation and CNA frequency in prostate cancer
patients. Table displaying the frequency of PIK3CA genetic mutation and copy number
alteration in prostate cancer patient genomic datasets (3-10). Data was accessed using the
Pik3ca mutation drives prostate cancer
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online cBioPortal cancer genomics platform (11,12). All samples were filtered for those that
have undergone sequencing and CNA analysis. A GISTIC putative copy number algorithm
was applied by the cBioPortal platform to establish high- and low-level copy number thresholds
to define samples with PIK3CA amplification or gain respectively (11,12).
Supplementary Table 2: Clinicopathological features of TCGA prostate adenocarcinoma
provisional dataset. Table summarizing key clinicopathological features of the TCGA
provisional prostate cancer patient dataset (obtained from the TCGA data portal https://tcga-
data.nci.nih.gov/).
Supplementary Table 3: PIK3CA mutation/amplification/gain frequency within the
TCGA prostate adenocarcinoma provisional dataset. Table outlining the correlation
between PIK3CA mutation and amplification/gain CNA with key clinicopathological features
in prostate cancer patient samples. Data was obtained from the TCGA data portal (https://tcga-
data.nci.nih.gov/). PIK3CA amplification/gain criteria; Log R ratio ≥ 0.135, probe number ≥
10. Silent mutations were excluded.
Supplementary Table 4: PTEN mutation/loss frequency within the TCGA prostate
adenocarcinoma provisional dataset. Table outlining the correlation between PTEN mutation
and CNA loss with key clinicopathological features in prostate cancer patient samples. Data
was obtained from the TCGA data portal (https://tcga-data.nci.nih.gov/). PTEN copy number
loss criteria; Log R ratio ≤ -0.48 for deletion, probe number ≥ 10. Silent mutations were
excluded.
Pik3ca mutation drives prostate cancer
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Supplementary Table 5: Phenotype summary of mouse histopathology. Table outlines the
histopathological phenotypes observed in Wt, Pik3ca+/HR, Ptenfl/fl and Pik3ca+/HR;Ptenfl/fl
cohorts at 56, 100, 200, 300 and 400 d of age.
Supplemental Table 6: RPPA antibody list. Table showing RPPA primary antibodies
categorised into signaling pathways.
Supplementary Table 7: RPPA analysis of prostate carcinoma response to castration
in Pik3ca+/HR, Ptenfl/fl and Pik3ca+/HR;Ptenfl/fl transgenic mice. Table indicates
proteins/phospho-proteins with statistically significant differences in Log2 normalised
mean RPPA signal intensities between the indicated genotype/treatment cohorts (unpaired
two-tail Welch’s t-test, P < 0.05, n = 3).
Supplementary Figure Legends
Supplementary Figure 1: PIK3CA mutations are predominantly missense mutations and
PTEN mutation/loss predicts for poor prostate cancer patient survival. (A) Pie chart
depicting the frequency of missense/nonsense mutations, in-frame deletions and fusion events
in PIK3CA identified in the 9 prostate cancer genomic datasets assessed in Fig. 1A (3-10). (B)
Kaplan-Meier plot comparing TCGA provisional prostate adenocarcinoma dataset with PTEN
homozygous deletion, loss or mutation compared to the general population. PTEN age-adjusted
COXPH HR: 0.47, P = 0.0026* (n = 492, samples with sequencing and CNA data only). Data
was obtained from the TCGA data portal (https://tcga-data.nci.nih.gov/). PTEN copy number
loss criteria; Log R ratio ≤ -0.48, probe number ≥ 10. Silent mutations were excluded.
Pik3ca mutation drives prostate cancer
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Supplementary Figure 2: Heterozygous Pik3caH1047R oncogenic mutation causes invasive
prostate cancer in mice that is phenotypically distinct to Pten-null prostate cancer. (A)
Sequencing cDNA isolated from PBiCre+/-;Pik3ca+/HR prostate tissue confirmed
heterozygosity at known silent base changes within mutant exon 20 adjacent to exon 19,
indicating recombination has occurred. (B) allele-specific PCR of cDNA isolated from
PBiCre+/- prostate tissue expressing either Pik3ca+/+ (Wt) or Pik3ca+/HR alleles (as previously
described (13)) revealed the presence of the mutant exon 20 in PBiCre+/-;Pik3ca+/HR prostate
cDNA, but not in PBiCre+/-;Wt prostate cDNA. (C) Representative H&E images of PBiCre+/-;
Wt, Pik3ca+/HR and Ptenfl/fl ventral and anterior prostate epithelium at 400 d (scale bar: 100 m).
Phenotype incidence plots for PBiCre+/-; Wt, Pik3ca+/HR and Ptenfl/fl ventral (D) and anterior
(E) prostate lobes. VP = Ventral prostate, AP = anterior prostate, PIN = prostate intraepithelial
neoplasia. (F) IHC to detect SMA in Wt, Pik3ca+/HR and Ptenfl/fl mice at 400 d (scale bar: 50
m). (G) Quantitation of PCNA-positive nuclei in PBiCre+/-; Pik3ca+/HR and Ptenfl/fl prostate
hyperplastic lesions. *P <0.001, one-way ANOVA with Tukey’s multiple comparison test, n =
3. Error bars: SEM.
Supplementary Figure 3: Characterization of Pik3ca-mutated and Pten-deleted prostate
hyperplasia and carcinoma. (A) IHC to detect the apoptotic marker Cleaved-Caspase-3
(CC3) in Wt, Pik3ca+/HR and Ptenfl/fl mice at 400 d (scale bar: 50 m). (B) Quantitation of CC3-
positive nuclei in Wt, Pik3ca+/HR and Ptenfl/fl prostate epithelium (n = 3, *P <0.05 compared to
Wt, or as indicated, one-way ANOVA with Tukey’s multiple comparison test, ns = not
significant. Error bars: SEM). (C) IHC to detect CK5 and CK8 in Pik3ca+/HR and Ptenfl/fl
carcinomas (representative images from 3 prostates per genotype, scale bar: 50 m). (D)
Representative IHC images to detect PTEN, mTORC1 signaling components (p-AKT Thr308,
p-RPS6 Ser235/236 and p-4E-BP1 Thr37/46) and mTORC2 substrates (p-AKT Ser473 and p-
Pik3ca mutation drives prostate cancer
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NDRG1 Thr346) in Pik3ca+/HR and Ptenfl/fl hyperplastic lesions (n = 3, scale bar: 50 m). IHC
quantitation for (E) p-AKT Thr308, (F) p-RPS6 Ser235/236, (G) p-4E-BP1 Thr37/46, (H) p-
AKT Ser473 and (I) p-NDRG1 Thr346 in Pik3ca+/HR and Ptenfl/fl prostate hyperplastic lesions
(n = 3, Error bars: SEM, *P < 0.05, unpaired, two-tailed t-test).
Supplementary Figure 4: Pik3caH1047R heterozygous oncogenic mutation causes p110-
dependent prostate cancer. Representative H&E images (scale bar: 100 m) for Pik3ca+/HR
and Ptenfl/fl dorsolateral prostate and histograms displaying phenotype incidence for anterior
(B) and ventral (C) prostate lobes from Pik3ca+/HR and Ptenfl/fl mice treated with vehicle, p110
inhibitor (A66), p110 inhibitor (TGX-221), pan-PI3K inhibitor (BKM120) or A66 + TGX-
221 for 4 weeks. ND = not done. A66 and TGX-221 were generated in house by P.R.S.
(University of Auckland, New Zealand) (14) and BKM120 was obtained from SYNkinase
(Australia).
Supplementary Figure 5: Pik3caH1047R mutation and Pten-deletion synergize to promote
prostate cancer by increasing mTORC1/2 signaling. Histograms displaying phenotype
incidence for anterior (A) and ventral (B) prostate lobes at 56 and 100 days of age. (C)
Representative IHC images of Pik3ca+/HR;Ptenfl/fl prostate tumors at 100 d stained to detect
CK8, CK5 and SMA (n = 3, scale bar: 50 m). (D) Bar chart displaying total prostate weight
normalised to body weight for Wt (n = 7), Pik3ca+/HR (n = 8), Ptenfl/fl (n = 8) and
Pik3ca+/HR;Ptenfl/fl (n = 7) 100 d old mice. Error bars: SEM, *P <0.05 compared to Wt or as
indicated, one-way ANOVA with Tukey’s multiple comparison test. (E) Quantitation of the
apoptotic marker Cleaved-Caspase-3 (CC3) positive nuclei and (F) representative IHC images
of CC3 staining in Pik3ca+/HR, Ptenfl/fl and Pik3ca+/HR;Ptenfl/fl stage-matched invasive prostate
carcinoma (scale bar: 50 m, n = 3, one-way ANOVA with Tukey’s multiple comparison test.
Pik3ca mutation drives prostate cancer
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Error bars: SEM). (G) Representative IHC images of Pik3ca+/HR, Ptenfl/fl and Pik3ca+/HR;Ptenfl/fl
stage-matched invasive prostate carcinoma stained to detect p-AKT Thr308, p-RPS6
Ser235/236, p-4E-BP1 Thr37/46, p-AKT Ser473 and p-NDRG1 Thr346 (scale bar: 50 m).
(H) Representative images of RNA in situ hybridisation (ISH) to detect positive (housekeeping
gene PPIB, peptidylprolyl isomerase B) and negative (bacterial gene dapB) control probes to
confirm RNA quality and the absence of background signal respectively (scale bar: 50 m,
insert scale bar: 5 m).
Supplementary Figure 6: Pik3ca+/HR and Ptenfl/fl prostate cancers acquire CRPC, while
Pik3ca+/HR;Ptenfl/fl mutants are resistant to castration. (A) Representative H&E images of
Pik3ca+/HR, Ptenfl/fl and Pik3ca+/HR;Ptenfl/fl anterior (AP) and ventral (VP) prostate lobes post-
castration (scale bar: 50 m, n = 3). (B) Representative IHC images of Pik3ca+/HR, Ptenfl/fl and
Pik3ca+/HR;Ptenfl/fl prostate tissue stained to detect Androgen receptor (AR) 2 weeks post-
castration compared to uncastrated, age-matched controls (scale bar: 50 m, n = 3). Mice were
castrated when prostate carcinoma was prevalent; Pik3ca+/HR = 400 d old, Ptenfl/fl = 200 d old
and Pik3ca+/HR;Ptenfl/fl = 100 d old. Insert displays positive AR nuclei (arrows) in
Pik3ca+/HR;Ptenfl/fl compound mutants (scale bar: 5 m). (C) Bar chart displaying total prostate
weight normalised to body weight for Pik3ca+/HR mice 0, 2 and 42 weeks post-castration (n =
8, 7 and 7, respectively). Error bars: SEM, *P <0.05 compared to 0 weeks post-castration, or
as indicated, one-way ANOVA with Tukey’s multiple comparison test. (D) Representative
H&E images of Pik3ca+/HR mice 0, 2 and 42 weeks post-castration (scale bar: 100 m). Mice
were castrated at 100 d of age.
Supplementary Figure 7: Characterization of Pik3ca+/HR, Ptenfl/fl and Pik3ca+/HR;Ptenfl/fl
prostate tumors. Representative images of IHC to detect (A) PCNA and (B) Cleaved-caspase
Pik3ca mutation drives prostate cancer
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3 (CC3) in Pik3ca+/HR, Ptenfl/fl and Pik3ca+/HR;Ptenfl/fl prostate tissue 2 weeks post-castration
compared to uncastrated, age-matched controls (scale bar: 50 m, n = 3). Mice were castrated
when prostate carcinoma was prevalent; Pik3ca+/HR = 400 d old, Ptenfl/fl = 200 d old and
Pik3ca+/HR;Ptenfl/fl =100 d old. Quantitative RT-PCR to detect (C) Nkx3.1 and (D) Pbsn mRNA
in Wt prostate and Pik3ca+/HR, Ptenfl/fl and Pik3ca+/HR;Ptenfl/fl stage-matched prostate
carcinomas (n = 5). Error bars: SEM, *P <0.05 compared to Wt, or as indicated, one-way
ANOVA with Tukey’s multiple comparison test. (E) Western Blotting of protein lysates
isolated from Wt prostate and stage-matched Pik3ca+/HR, Ptenfl/fl and Pik3ca+/HR;Ptenfl/fl
prostate carcinomas to detect total AKT, p-AKT Thr308 and p-AKT Ser473 (n = 3).
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Supplementary Table 1. PIK3CA mutation/CNA frequency in prostate cancer patients
Alteration No. of patients (%)
Neuroendocrine prostate cancer, Beltran et al, Nat Med 2016 (n = 77)
Mutation 1 (1.3%)
Amplification 22 (28.6%)
Gain 26 (33.8%)
Total 49 (63.6%)
Prostate adenocarcinoma, Kumar et al, Nat Med 2016 (n = 54)
Mutation 2 (3.7%)
Amplification 4 (7.4%)
Gain 19 (35.2%)
Total 25 (46.3%)
Prostate adenocarcinoma vs. Metastatic, Grasso et al, Nature 2012 (n = 59)
Mutation 0 (0.0%)
Amplification 6 (10.2%)
Gain 14 (23.7%)
Total 20 (33.9%)
Prostate adenocarcinoma, Baca et al, Cell 2013 (n = 56)
Mutation 2 (3.6%)
Amplification 2 (3.6%)
Gain 8 (14.3%)
Total 12 (21.4%)
TCGA prostate adenocarcinoma provisional dataset (n = 492)
Mutation 14 (2.9%)
Amplification 13 (2.6%)
Gain 60 (12.2%)
Total 86 (17.7%)* *2 patients displayed 2 PIK3CA mutations (E542A+N345I and R108C+L569I), 1 case had E542K mutation and gain.
Prostate adenocarcinoma TCGA, Cell 2015 (n = 333)
Mutation 6 (1.8%)**
Amplification 5 (1.5%)
Gain 47 (14.1%)
Total 58 (17.4%)
**1 patient displayed 2 PIK3CA mutations (case 1: E542A+N345I)
Prostate adenocarcinoma, Barbieri et al, Nat Genetics 2012 (n = 109)
Mutation 4 (3.7%)
Amplification 1 (0.9%)
Gain 14 (12.8%)
Total 19 (17.4%)
Prostate adenocarcinoma, Taylor et al, Cancer Cell 2010 (n = 103)
Mutation 3 (2.9%)
Amplification 0 (0.0%)
Gain 9 (8.7%)
Total 12 (11.7%)
Metastatic prostate cancer, Robinson et al, Cell 2015 (n = 150)
Mutation 6 (4.0%)
Amplification 1 (0.7%)
Gain 0 (0.0%)
Fusion + amplification 1 (0.7%)
Total 8 (5.3%)
Supplementary Table 2 Clinicopathological features of TCGA prostate adenocarcinoma provisional dataset
Characteristic
Sample size (n)
Follow-up (months)
492
Mean 20.9
Median 14.6
Range 0.03-151
Age (years)
<50 27
50-60 175
60-70 240
>70 50
Post-treatment PSA (ng/ml)
<4 409
4-10 10
10-20 11
>20 5
N/A 57
pT category
pT2 187
pT3a 156
pT3b 132
pT4 10
N/A 7
Gleason grade
≤3+3 44
3+4 154
4+3 106
≥4+4 188
Regional lymph node metastasis
pN0 343
pN+ 77
N/A 72
Supplementary Table 3 PIK3CA mutation/amplification/gain analysis of TCGA prostate cancer provisional dataset.
†P-value = Fisher’s exact test between PIK3CA mutation/amplification/gain and the general population. ††Two mutations occurred in the same patient in 2 cases (R108C+L569I and E542A+N345I). †††One PIK3CA mutant carrier also displayed a gain in PIK3CA copy number.
Characteristic n
PIK3CA
mutation
n (%)
PIK3CA
amplification/gain
n (%)
PIK3CA mutation/
amplification/gain
n (%)
General
population
n (%)
P value†
All Samples 492 14 (3%)†† 73 (15%)††† 86 (17%) 406 (83%)
Regional lymph node
metastasis
pN0 10 (71%) 43 (59%) 52 (60%) 291 (72%) 0.0004*
pN+ 1 (7%) 25 (34%) 26 (30%) 51 (13%)
N/A 3 (21%) 5 (7%) 8 (9%) 64 (16%)
pT category
pT2 3 (21%) 12 (16%) 15 (17%) 172 (42%) <0.0001*
pT3a 6 (43%) 25 (34%) 31 (36%) 125 (31%)
pT3b 5 (36%) 30 (41%) 34 (40%) 98 (24%)
pT4 0 (0%) 4 (5%) 4 (5%) 6 (1%)
N/A 0 (0%) 2 (3%) 2 (2%) 5 (1%)
Gleason grade
≤3+3 0 (0%) 1 (1%) 1 (1%) 43 (11%) <0.0001*
3+4 3 (21%) 8 (11%) 11 (13%) 143 (35%)
4+3 1 (7%) 11 (15%) 12 (14%) 94 (23%)
≥4+4 10 (71%) 53 (73%) 62 (72%) 126 (31%)
Post-treatment PSA
(ng/ml)
<4 10 (71%) 56 (77%) 65 (76%) 344 (85%) 0.05
4-10 0 (0%) 3 (4%) 3 (3%) 7 (2%)
10-20 1 (7%) 1 (1%) 2 (2%) 9 (2%)
>20 0 (0%) 3 (4%) 3 (3%) 2 (0%)
N/A 3 (21%) 10 (14%) 13 (15%) 44 (11%)
Supplementary Table 4 PTEN mutation/loss analysis of TCGA prostate cancer provisional dataset.
†P-value = Fisher’s exact test between PTEN mutation/loss and the general population. ††Seven patients carried a PTEN mutation and PTEN copy number loss.
Characteristic n
PTEN
mutation
n (%)
PTEN
loss
n (%)
PTEN
mutation/loss
n (%)
General
population
n (%)
P value†
All Samples† 492 17 (3%) 95 (19%) 105 (21%)†† 387 (79%)
Regional lymph node
metastasis
pN0 14 (82%) 64 (67%) 73 (70%) 270 (70%) 0.0028*
pN+ 2 (12%) 25 (26%) 25 (24%) 52 (13%)
N/A 1 (6%) 6 (6%) 7 (7%) 65 (17%)
pT category
pT2 7 (41%) 16 (17%) 21 (20%) 166 (43%) <0.0001*
pT3a 6 (35%) 36 (38%) 38 (36%) 118 (30%)
pT3b 4 (24%) 40 (42%) 43 (41%) 89 (23%)
pT4 0 (0%) 2 (2%) 2 (2%) 8 (2%)
N/A 0 (0%) 1 (1%) 1 (1%) 6 (2%)
Gleason grade
≤3+3 0 (0%) 5 (5%) 5 (5%) 39 (10%) 0.0006*
3+4 6 (35%) 17 (18%) 22 (21%) 132 (34%)
4+3 3 (18%) 19 (20%) 20 (19%) 86 (22%)
≥4+4 8 (47%) 54 (57%) 58 (55%) 130 (34%)
Post-treatment PSA
(ng/ml)
<4 14 (82%) 79 (83%) 87 (83%) 322 (83%) 0.24
4-10 0 (0%) 3 (3%) 3 (3%) 7 (2%)
10-20 1 (6%) 2 (2%) 2 (2%) 9 (2%)
>20 0 (0%) 3 (3%) 3 (3%) 2 (1%)
N/A 2 (12%) 8 (8%) 10 (10%) 47 (12%)
Age Genotype N
Prostate
hyperplasia
N (%)
Prostate
neoplasia
N (%)
Prostate
carcinoma
N (%)
Seminal vesicle
neoplasia
N (%)
Urethra
neoplasia
N (%)
Adrenal
pheochromocytoma
N (%)
56 d Wt 8 0 0 0 0 0 0
Pik3ca+/HR 9 0 0 0 0 0 0
Ptenfl/fl 7 7/7 (100%) 0 0 0 0 0
Pik3ca+/HR;Ptenfl/fl 5 0 1/5 (20%) 4/5 (80%) 1/5 (20%) 0 5/5 (100%)
100 d Wt 7 0 0 0 0 0 0
Pik3ca+/HR 8 6/8 (75%) 0 0 0 0 0
Ptenfl/fl 8 0 8/8 (100%) 0 0 0 3/8 (38%)
Pik3ca+/HR;Ptenfl/fl 7 0 0 7/7 (100%) 7/7 (100%) 5/7 (71%) 7/7 (100%)
200 d Wt 8 0 0 0 0 0 0
Pik3ca+/HR 8 7/8 (88%) 0 0 0 0 0
Ptenfl/fl 7 0 2/7 (29%) 5/7 (71%) 1/7 (14%) 0 4/7 (57%)
300 d Wt 7 0 0 0 0 0 0
Pik3ca+/HR 8 0 2/8 (25%) 6/8 (75%) 0 0 0
Ptenfl/fl 7 0 1/7 (14%) 6/7 (86%) 4/6 (67%) 1/6 (17%) 5/6 (83%)
400 d Wt 17 0 0 0 0 0 0
Pik3ca+/HR 17 2/17 (12%) 0 15/17 (88%) 2/17 (12%) 0 0
Ptenfl/fl 8 0 0 8/8 (100%) 5/8 (63%) 2/8 (25%) 7/8 (88%)
Supplementary Table 5: Phenotype summary of mouse histopathology
Antibody Source Cat.# Host
PI3K/mTOR Pathway
AKT Cell Signaling Technology 9272 Rabbit
p-AKT (S473) Cell Signaling Technology 4060 Rabbit
p-AKT (T308) Cell Signaling Technology 2965 Rabbit
AMPK Cell Signaling Technology 8208 Rabbit
p-AMPK Cell Signaling Technology 8208 Rabbit
4E-BP1 Cell Signaling Technology 9452 Rabbit
p-4E-BP1 (T37/T46) Cell Signaling Technology 9459 Rabbit
FOXO3A Cell Signaling Technology 2497 Rabbit
p-FOXO3A (S253) Cell Signaling Technology 9466 Rabbit
p-FOXO3A (S318/S321) Cell Signaling Technology 9465 Rabbit
GSK-3 Cell Signaling Technology 9315 Rabbit
p-GSK-3S9 Cell Signaling Technology 9336 Rabbit
PI3K p110 Cell Signaling Technology 4255 Rabbit
PI3K p110(clone C73F8) Cell Signaling Technology 4249 Rabbit
PI3K p110 Cell Signaling Technology 3011 Rabbit
p-PDK1 (S241) Cell Signaling Technology 3061 Rabbit
p-PKC (pan) (II S660) Cell Signaling Technology 9371 Rabbit
p-PKC Cell Signaling Technology 9378 Rabbit
PTEN Cell Signaling Technology 9552 Rabbit
p-PTEN (S380/T382/T383) Cell Signaling Technology 9554 Rabbit
MTOR Cell Signaling Technology 2972 Rabbit
p-MTOR (S2448) Cell Signaling Technology 2971 Rabbit
NDRG1 Cell Signaling Technology 5196 Rabbit
p-NDRG1 (T346) Cell Signaling Technology 3217 Rabbit
RPS6 Cell Signaling Technology 2217 Rabbit
p-RPS6 (S235/S236) Cell Signaling Technology 2211 Rabbit
p-RPS6 (S240/S244) Cell Signaling Technology 2215 Rabbit
SGK1 Cell Signaling Technology 12103 Rabbit
TSC2 Cell Signaling Technology 3612 Rabbit
p-TSC2 (T1462) Cell Signaling Technology 3617 Rabbit
Tyrosine kinase-mediated pathways
EGFR Cell Signaling Technology 2232 Rabbit
p-EGFR (Y1173) Cell Signaling Technology 4407 Rabbit
p-ErbB2/HER2 (Y1248)/EGFR (Y1173) Cell Signaling Technology 2244 Rabbit
p-ErbB2/HER2 (Y877) Cell Signaling Technology 2241 Rabbit
Supplementary Table 6. RPPA antibody list
IRS-1 Cell Signaling Technology 2382 Rabbit
p-IRS-1 (S636/S639) Cell Signaling Technology 2388 Rabbit
IGF-1R Cell Signaling Technology 3018 Rabbit
p-SHP-2 (Y542) Cell Signaling Technology 3751 Rabbit
p-MET (Y1234, Y1235) Cell Signaling Technology 3129 Rabbit
SRC Cell Signaling Technology 2109 Rabbit
p-SRC family (Y416) Cell Signaling Technology 2101 Rabbit
MAPK Pathway
ERK1/2 Cell Signaling Technology 9102 Rabbit
p-ERK1/2 (T202/Y204) Cell Signaling Technology 9101 Rabbit
p-c-RAF (S338) Cell Signaling Technology 9427 Rabbit
p-SHC (Y317) Cell Signaling Technology 2431 Rabbit
p-SHC (Y239/Y240) Cell Signaling Technology 2434 Rabbit
p-c-JUN (S73) Cell Signaling Technology 9164 Rabbit
p38 MAPK Cell Signaling Technology 9212 Rabbit
p-p38 MAPK (T180/Y182) Cell Signaling Technology 4631 Rabbit
JAK/STAT signaling
p-STAT1 (Y701) Cell Signaling Technology 7649 Rabbit
STAT3 Cell Signaling Technology 4904 Rabbit
p-STAT3 (Y705) Cell Signaling Technology 9131 Rabbit
p-STAT5 (Y694) Cell Signaling Technology 9351 Rabbit
Hippo Signaling
TAZ Cell Signaling Technology 4883 Rabbit
YAP Cell Signaling Technology 4912 Rabbit
p-YAP (S127) Cell Signaling Technology 13008 Rabbit
NF-B signaling
IB Cell Signaling Technology 4812 Rabbit
p-IB(S32) Cell Signaling Technology 2859 Rabbit
NF-B p65 Cell Signaling Technology 4764 Rabbit
p-NF-B p65 (S536) Cell Signaling Technology 3031 Rabbit
p-IKK/(S176/S180) Cell Signaling Technology 2694 Rabbit
Wnt Signalling
-catenin Cell Signaling Technology 9562 Rabbit
p--catenin (S33/S37/T41) Cell Signaling Technology 9561 Rabbit
p--catenin (T41/S45) Cell Signaling Technology 9565 Rabbit
DNA repair
ATM Cell Signaling Technology 2873 Rabbit
p-ATM/ATR (S/T) Substrate Cell Signaling Technology 2851 Rabbit
Apoptosis Pathway
Caspase-3 Cell Signaling Technology 9662 Rabbit
Cleaved Caspase-3 (D175) Cell Signaling Technology 9664 Rabbit
Cleaved Caspase-7 (D198) Cell Signaling Technology 9491 Rabbit
p-BAD (S112) Cell Signaling Technology 9291 Rabbit
p-BAD (S136) Cell Signaling Technology 9295 Rabbit
PARP Cell Signaling Technology 9542 Rabbit
Cell Cycle regulator
p21 (WAF1/CIP1) Cell Signaling Technology 2947 Rabbit
p27 Cell Signaling Technology 3686 Rabbit
p53 Cell Signaling Technology 9282 Rabbit
p-p53 (S15) Cell Signaling Technology 9284 Rabbit
p-AURORA A/B/C (T288;T232;T198) Cell Signaling Technology 2914 Rabbit
CDK2 Cell Signaling Technology 2546 Rabbit
Cyclin D1 Cell Signaling Technology 2978 Rabbit
p-CDC2 (Y15) Cell Signaling Technology 9111 Rabbit
c-MYC Cell Signaling Technology 5605 Rabbit
Other
-Actin Cell Signaling Technology 4970 Rabbit
CK2 Cell Signaling Technology 2656 Rabbit
CREB Cell Signaling Technology 9197 Rabbit
E-cadherin Cell Signaling Technology 3195 Rabbit
FAK Cell Signaling Technology 3285 Rabbit
p-FAK (Y397) Cell Signaling Technology 3283 Rabbit
p-HDAC 4/5/7 (S246;S259;S155) Cell Signaling Technology 3443 Rabbit
ROCK1 Cell Signaling Technology 4035 Rabbit
RAP1A/RAP1B Cell Signaling Technology 4938 Rabbit
p-SMAD2/3 (S465/S467;S423/S425) Cell Signaling Technology 8828 Rabbit
p-VEGFR2 (Y1059) Cell Signaling Technology 3817 Rabbit
p-VEGFR2 (Y1175) Cell Signaling Technology 2478 Rabbit
ZAP-70 Cell Signaling Technology 2705 Rabbit
Supplementary Table 7. RPPA analysis of prostate carcinoma response to castration in
Pik3ca+/HR, Ptenfl/fl and Pik3ca+/HR;Ptenfl/fl transgenic mice.
Protein/phospho-protein
Difference
in means†
P-value††
Pathway
Pik3ca+/HR vs Ptenfl/fl (uncastrated)
p-AKT (S473) 2.4437 0.00107 PI3K/mTOR p-AKT (T308) 1.4475 0.00211 PI3K/mTOR
p-FOX03A (S318/S321) 0.8597 0.04955 PI3K/mTOR
P-GSK-3 (S9) 2.0837 0.01230 PI3K/mTOR
PI3K p110 0.5628 0.02644 PI3K/mTOR
PI3K p110 (C73F8) 0.9666 0.00704 PI3K/mTOR
p-PDK1 (S241) 0.7877 0.03018 PI3K/mTOR PTEN 1.1412 0.03575 PI3K/mTOR
p-NDRG1 (T346) 1.5167 0.00478 PI3K/mTOR p-RPS6 (S240/S244) 1.0442 0.04917 PI3K/mTOR
TSC2 0.5981 0.04178 PI3K/mTOR
p-TSC2_(T1462) 1.5832 0.00414 PI3K/mTOR p-EGFR (Y1173) 0.7856 0.03456 Tyrosine kinase
IGF-1R 0.4104 0.02872 Tyrosine kinase p-SHP-2 (Y542) 2.3159 0.02446 Tyrosine kinase
p-SRC family (Y416) 2.7902 0.00627 Tyrosine kinase ERK1/2 0.8449 0.03442 MAPK
p-ERK1/2 (T202/Y204) 0.8334 0.03396 MAPK
p38 MAPK 1.4115 0.00122 MAPK p-p38 MAPK (T180, Y182) 0.9041 0.01873 MAPK
STAT3 0.8745 0.00396 JAK/STAT
IkB 0.9134 0.00712 NF-kB
NF-B p65 1.0817 0.03051 NF-kB
p--catenin (T41, S45) 0.5404 0.01435 Wnt
Caspase 3 0.9378 0.02699 Apoptosis Cleaved Caspase 3 (D175) 2.1374 0.03710 Apoptosis
p-BAD (S136) 0.7902 0.03906 Apoptosis p53 0.5471 0.02037 Cell Cycle
p-p53 (S15) 1.0223 0.02844 Cell Cycle
p-CDC2 (Y15) 1.9320 0.02961 Cell Cycle c-MYC 0.8257 0.00658 Cell Cycle
-Actin 2.2433 0.03791 Other p-VEGFR2 (Y1175) 1.6929 0.04150 Other
Pik3ca+/HR; Ptenfl/fl vs Pik3ca+/HR (uncastrated)
p-AKT (S473) 2.7871 0.01497 PI3K/mTOR
p-GSK-3 (S9) 1.8298 0.02440 PI3K/mTOR
p-NDRG1 (T346) 2.5913 0.00520 PI3K/mTOR
p-RPS6 (S240, S244) 9.3709 0.00605 PI3K/mTOR TSC2 0.7634 0.03142 PI3K/mTOR
p-ErbB2/HER2 (Y1248)/EGFR (Y1173) 10.1726 0.00424 Tyrosine kinase
p-SHP-2 (Y542) 11.7934 0.00134 Tyrosine kinase
SRC 1.3873 0.01029 Tyrosine kinase p-SRC (Y416) 13.009 0.00092 Tyrosine kinase
p38 MAPK 1.5542 0.01955 MAPK STAT3 0.8734 0.02893 JAK/STAT
p-STAT3 (Y705) 4.4402 0.02730 JAK/STAT
YAP 0.7721 0.02979 Hippo
NF-B p65 1.1489 0.03293 NF-kB
p-NF-B p65 (S536) 1.0470 0.03711 NF-kB
Caspase 3 0.7702 0.04155 Apoptosis
Cleaved Caspase 7 (D198) 7.6335 0.01754 Apoptosis p-Bad (S136) 1.3859 0.04272 Apoptosis
CDK2 0.8615 0.00224 Cell Cycle p-CDC2 (Y15) 11.0603 0.03132 Cell Cycle
-Actin 3.5345 0.01278 Other E-Cadherin 1.0714 0.03975 Other
Pik3ca+/HR; Ptenfl/fl vs Ptenfl/fl (uncastrated) AKT 0.5279 0.02408 PI3K/mTOR PTEN 0.8471 0.01546 PI3K/mTOR p-NDRG1 (T346) 1.0746 0.02542 PI3K/mTOR
p-RPS6 (S240, S244) 8.3267 0.01044 PI3K/mTOR
p-SHP-2 (Y542) 9.4775 0.00265 Tyrosine kinase p-SRC (Y412) 10.2188 <0.0001 Tyrosine kinase p-SHC (Y317) 0.8568 0.03593 Tyrosine kinase p-c-JUN (S73) 8.9696 0.00265 MAPK TAZ 0.4354 0.03794 Hippo Cleaved Caspase 7 (D198) 10.1273 0.00046 Apoptosis p-Bad (S136) 2.1761 0.01242 Apoptosis p-CDC2 (Y15) 9.1283 0.04929 Cell Cycle
-Actin 1.2912 0.00203 Other
E-Cadherin 1.5434 0.02583 Other
p-VEGFR2 (Y1059) 2.0316 0.00677 Other
p-VEGFR2 (Y1175) 3.4998 0.01987 Other
Pik3ca+/HR uncastrated vs Pik3ca+/HR castrated
mTOR 1.0502 0.01399 PI3K/mTOR
p-RPS6 (S240/S244) 5.9486 0.00896 PI3K/mTOR
p-TSC2 (T1462) 0.9590 0.01251 PI3K/mTOR
IGF-1R 0.4778 0.03151 Tyrosine kinase
IB 0.9337 0.03718 NF-B
p-NF-kB p65 (S536) 0.8596 0.04852 NF-B
p53 0.4184 0.04522 Cell cycle
CDK2 0.5662 0.01951 Cell cycle
RAP1A/RAP1B 0.9213 0.03866 Other
Ptenfl/fl uncastrated vs Ptenfl/fl castrated
p-AMPK 0.9451 0.04425 PI3K/mTOR
p-FOXO3A (S318/S321) 0.7328 0.02036 PI3K/mTOR
GSK-3 0.6393 0.03958 PI3K/mTOR
p-GSK-3S9 0.5814 0.04957 PI3K/mTOR
PI3K p110 (C73F8) 0.5006 0.04358 PI3K/mTOR
p-PKC 0.8070 0.04234 PI3K/mTOR
p-TSC2 (T1462) 0.7835 0.04773 PI3K/mTOR
IRS-1 1.0606 0.03694 Tyrosine kinase
ERK1/2 0.6510 0.04475 MAPK
p-c-RAF (S338) 0.5344 0.03642 MAPK
p38 MAPK 0.6484 0.0479 MAPK
Caspase 3 0.6075 0.03098 Apoptosis
CDK2 0.6562 0.02779 Cell Cycle
Pik3ca+/HR;Ptenfl/fl uncastrated vs Pik3ca+/HR;Ptenfl/fl castrated
p-SHP-2 (Y542) 9.2513 0.00054 Tyrosine kinase
p-SRC (Y416) 9.3157 0.00063 Tyrosine kinase
YAP 0.3805 0.03192 Hippo
CK2 0.3346 0.00985 Other
Pik3ca+/HR vs Ptenfl/fl (castrated)
AKT 1.5906 0.02614 PI3K/mTOR
AMPK 1.1520 0.03527 PI3K/mTOR
FOXO3A 2.3281 0.00609 PI3K/mTOR
p-FOXO3A (S318/S321) 2.2829 0.00528 PI3K/mTOR
PI3K p110 0.3448 0.02069 PI3K/mTOR
PTEN 2.0117 0.02173 PI3K/mTOR
p-NDRG1 (T346) 1.3790 <0.0001 PI3K/mTOR
IRS-1 1.7688 0.01342 Tyrosine Kinase
SRC 1.6332 0.03586 Tyrosine Kinase
p-ERK1/2 (T202, Y204) 1.9048 0.02239 MAPK
p-c-RAF (S338) 0.8342 0.03993 MAPK
p-SHC (Y317) 1.3861 0.03662 MAPK
p-STAT3 (Y705) 2.3954 0.04674 JAK/STAT
p-NF-B p65(S536) 1.0298 0.04484 NF-kB
p-ATM/ATR (S/T) Substrate 2.5925 0.04121 DNA repair
CDK2 0.7670 0.00730 Cell Cycle
CK2 1.2165 0.00651 Other
RAP1A/RAP1B 1.1846 0.01925 Other
p-VEGFR2 (Y1175) 3.0430 0.02767 Other
Pik3ca+/HR; Ptenfl/fl vs Pik3ca+/HR (castrated)
p-AKT (473) 1.9109 0.03118 PI3K/mTOR
FOXO3A 1.2664 0.02862 PI3K/mTOR
MTOR 1.1556 0.00943 PI3K/mTOR
p-NDRG1 (T346) 2.3525 0.00012 PI3K/mTOR
SRC 1.9918 0.02073 Tyrosine kinase
p-SRC (Y416) 3.3642 0.02960 Tyrosine kinase
p-STAT3 (Y705) 3.2727 0.01735 JAK/STAT
PARP 1.8056 0.02269 Apoptosis
p53 0.3799 0.04869 Cell Cycle
p-CDC2 (Y15) 4.8288 0.01469 Cell Cycle
-Actin 2.1633 0.03093 Other
E-Cadherin 2.1185 0.00483 Other
RAP1A/RAP1B 1.5625 0.03034 Other
Pik3ca+/HR; Ptenfl/fl vs Ptenfl/fl (castrated)
p-AMPK 1.3287 0.02707 PI3K/mTOR
FOXO3A 1.0617 0.01107 PI3K/mTOR
p-FOXO3A (S318/S321) 1.2952 0.03103 PI3K/mTOR
p-PKC 0.8743 0.04833 PI3K/mTOR
PTEN 1.0459 0.02067 PI3K/mTOR
NDRG1 1.1792 0.02267 PI3K/mTOR
p-NDRG1 (T346) 0.9735 0.00145 PI3K/mTOR
RPS6 1.8945 0.00819 PI3K/mTOR
p-RPS6 (S240/244) 4.6657 0.03675 PI3K/mTOR
p-ErbB2/HER2 (Y1248)/EGFR (Y1173) 7.0385 0.00244 Tyrosine kinase
p-SHC (Y317) 1.2112 0.01602 MAPK
p-c-JUN (S73) 9.8366 0.00011 MAPK
TAZ 0.4362 0.03212 Hippo
ATM 8.5576 0.00651 DNA repair
p-BAD (S136) 1.0201 0.01941 Apoptosis
-Actin 2.2330 0.02836 Other
CK2 0.7012 0.04958 Other †Absolute means difference calculated from Log2 normalised and median centred data. ††P-value <0.05 filtered data; unpaired, two-tailed Welch’s t test (n = 3).
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