Supplementary Figures S1-S4 from Trastuzumab and Pertuzumab Produce Changes in Morphology and Estrogen Receptor Signaling in Ovarian Cancer Xenografts Revealing New Treatment Strategies

Supplementary Figure Legends 1-3 from Tyrosine Phosphorylation Profiling Reveals the Signaling Network Characteristics of Basal Breast Cancer Cells

Supplementary Figure 1 from Tyrosine Phosphorylation Profiling Reveals the Signaling Network Characteristics of Basal Breast Cancer Cells

Supplementary Table 5 from Tyrosine Phosphorylation Profiling Reveals the Signaling Network Characteristics of Basal Breast Cancer Cells

Supplementary Table 4 from Tyrosine Phosphorylation Profiling Reveals the Signaling Network Characteristics of Basal Breast Cancer Cells

Supplementary Figure 3 from Tyrosine Phosphorylation Profiling Reveals the Signaling Network Characteristics of Basal Breast Cancer Cells

Supplementary Figure 2 from Tyrosine Phosphorylation Profiling Reveals the Signaling Network Characteristics of Basal Breast Cancer Cells

Supplementary Data from PPM1D Is a Potential Therapeutic Target in Ovarian Clear Cell Carcinomas

Supplementary Information from Systems Biology Reveals New Strategies for Personalizing Cancer Medicine and Confirms the Role of PTEN in Resistance to Trastuzumab

Current clinical practice in cancer stratifies patients based on tumour histology to determine prognosis. Molecular profiling has been hailed as the path towards personalised care, but molecular data are still typically analysed independently of known clinical information. Conventional clinical and histopathological data, if used, are added only to improve a molecular prediction, placing a high burden upon molecular data to be informative in isolation. Here, we develop a novel Monte Carlo analysis to evaluate the usefulness of data assemblages. We applied our analysis to varying assemblages of clinical data and molecular data in an ovarian cancer dataset, evaluating their ability to discriminate one-year progression-free survival (PFS) and three-year overall survival (OS). We found that Cox proportional hazard regression models based on both data types together provided greater discriminative ability than either alone. In particular, we show that proteomics data assemblages that alone were uninformative (p = 0.245 for PFS, p = 0.526 for OS) became informative when combined with clinical information (p = 0.022 for PFS, p = 0.048 for OS). Thus, concurrent analysis of clinical and molecular data enables exploitation of prognosis-relevant information that may not be accessible from independent analysis of these data types.

Selecting colorectal cancer (CRC) patients likely to respond to therapy remains a clinical challenge. The objectives of this study were to establish which genes were differentially expressed with respect to treatment sensitivity and relate this to copy number in a panel of 15 CRC cell lines. Copy number variations of the identified genes were assessed in a cohort of CRCs. IC50’s were measured for 5-fluorouracil, oxaliplatin, and BEZ-235, a PI3K/mTOR inhibitor. Cell lines were profiled using array comparative genomic hybridisation, Illumina gene expression analysis, reverse phase protein arrays, and targeted sequencing of KRAS hotspot mutations. Frequent gains were observed at 2p, 3q, 5p, 7p, 7q, 8q, 12p, 13q, 14q, and 17q and losses at 2q, 3p, 5q, 8p, 9p, 9q, 14q, 18q, and 20p. Frequently gained regions contained EGFR, PIK3CA, MYC, SMO, TRIB1, FZD1, and BRCA2, while frequently lost regions contained FHIT and MACROD2. TRIB1 was selected for further study. Gene enrichment analysis showed that differentially expressed genes with respect to treatment response were involved in Wnt signalling, EGF receptor signalling, apoptosis, cell cycle, and angiogenesis. Stepwise integration of copy number and gene expression data yielded 47 candidate genes that were significantly correlated. PDCD6 was differentially expressed in all three treatment responses. Tissue microarrays were constructed for a cohort of 118 CRC patients and TRIB1 and MYC amplifications were measured using fluorescence in situ hybridisation. TRIB1 and MYC were amplified in 14.5% and 7.4% of the cohort, respectively, and these amplifications were significantly correlated (p≤0.0001). TRIB1 protein expression in the patient cohort was significantly correlated with pERK, Akt, and Caspase 3 expression. In conclusion, a set of candidate predictive biomarkers for 5-fluorouracil, oxaliplatin, and BEZ235 are described that warrant further study. Amplification of the putative oncogene TRIB1 has been described for the first time in a cohort of CRC patients.

Proteomic profiling of the estrogen/tamoxifen-sensitive MCF-7 cell line and its partially sensitive (MCF-7/LCC1) and fully resistant (MCF-7/LCC9) variants was performed to identify modifiers of endocrine sensitivity in breast cancer. Analysis of the expression of 120 paired phosphorylated and non-phosphorylated epitopes in key oncogenic and tumor suppressor pathways revealed that STAT1 and several phosphorylated epitopes (phospho-STAT1(Tyr701) and phospho-STAT3(Ser727)) were differentially expressed between endocrine resistant and parental controls, confirmed by qRT-PCR and western blotting. The STAT1 inhibitor EGCG was a more effective inhibitor of the endocrine resistant MCF-7/LCC1 and MCF-7/LCC9 lines than parental MCF-7 cells, while STAT3 inhibitors Stattic and WP1066 were equally effective in endocrine-resistant and parental lines. The effects of the STAT inhibitors were additive, rather than synergistic, when tested in combination with tamoxifen in vitro. Expression of STAT1 and STAT3 were measured by quantitative immunofluorescence in invasive breast cancers and matched lymph nodes. When lymph node expression was compared to its paired primary breast cancer expression, there was greater expression of cytoplasmic STAT1 (∼3.1 fold), phospho-STAT3(Ser727) (∼1.8 fold), and STAT5 (∼1.5 fold) and nuclear phospho-STAT3(Ser727) (∼1.5 fold) in the nodes. Expression levels of STAT1 and STAT3 transcript were analysed in 550 breast cancers from publicly available gene expression datasets (GSE2990, GSE12093, GSE6532). When treatment with tamoxifen was considered, STAT1 gene expression was nearly predictive of distant metastasis-free survival (DMFS, log-rank p = 0.067), while STAT3 gene expression was predictive of DMFS (log-rank p<0.0001). Analysis of STAT1 and STAT3 protein expression in a series of 546 breast cancers also indicated that high expression of STAT3 protein was associated with improved survival (DMFS, p = 0.006). These results suggest that STAT signaling is important in endocrine resistance, and that STAT inhibitors may represent potential therapies in breast cancer, even in the resistant setting.

Background: Steroid receptor coactivator 3 (SRC3) is an important coactivator of a number of transcription factors and is associated with a poor outcome in numerous tumours. Steroid receptor coactivator 3 is amplified in 25% of epithelial ovarian cancers (EOCs) and its expression is higher in EOCs compared with non-malignant tissue. No data is currently available with regard to the expression of SRC-3 in EOC and its influence on outcome or the efficacy of treatment. Methods: Immunohistochemistry was performed for SRC3, oestrogen receptor- α , HER2, PAX2 and PAR6, and protein expression was quantified using automated quantitative immunofluorescence (AQUA) in 471 EOCs treated between 1991 and 2006 with cytoreductive surgery followed by first-line treatment platinum-based therapy, with or without a taxane. Results: Steroid receptor coactivator 3 expression was significantly associated with advanced stage and was an independent prognostic marker. High expression of SRC3 identified patients who have a significantly poorer survival with single-agent carboplatin chemotherapy, while with carboplatin/paclitaxel treatment such a difference was not seen. Conclusion: Steroid receptor coactivator 3 is a poor prognostic factor in EOCs and appears to identify a population of patients who would benefit from the addition of taxanes to their chemotherapy regimen, due to intrinsic resistance to platinum therapy.

BACKGROUND:Anti-estrogen therapy appears to have efficacy in a subset of ovarian cancers, as demonstrated in multiple phase II studies. Identifying sensitive patients early in treatment may allow for targeted, low-toxicity primary therapy or prevention of recurrence. We have previously demonstrated that the likelihood of response to letrozole could be improved by patient selection based on estrogen-pathway marker expression. We sought to identify ovarian cancer biomarkers that might indicate sensitivity to fulvestrant, an estrogen receptor antagonist.METHODS:Tissue samples from the primary tumors of patients enrolled in a phase II study of fulvestrant for the treatment of multiply-recurrent ovarian cancer were embedded randomly in a tissue microarray (TMA). Estrogen receptor alpha (ERα) expression was assessed by both conventional immunohistochemistry (IHC) and quantitative immunofluorescence (IF) (AQUA) while expression of 14 other estrogen-regulated markers was assessed by quantitative IF and correlated with clinical outcomes.RESULTS:Almost half of patients experienced clinical benefit (CR+PR+SD) at 90 days despite a median of 5 previous treatment regimens. 24 of 26 patient samples were available and included in the TMA. ERα expression, measured either by conventional IHC or by AQUA analysis, was associated with clinical benefit, while TFF1 and vimentin expression (measured by IF AQUA score) was predictive of progression-free survival.CONCLUSIONS:These results confirm our previous observation that clinical ovarian cancer includes a subset of tumors with sensitivity to estrogen pathway blockade. Expression profile of sensitive tumors appears to be detectably different from insensitive tumors, suggesting that further improvements in treatment efficacy can be obtained through appropriate patient selection.

Objective—Using a clinical model of deep arterial injury, we assessed the ability of exogenous and endogenous tissue plasminogen activator (t-PA) to limit acute in situ thrombus formation. Approach and Results—Ex vivo thrombus formation was assessed in the Badimon chamber at low and high shear rates in 2 double-blind randomized cross-over studies of 20 healthy volunteers during extracorporeal administration of recombinant t-PA (0, 40, 200, and 1000 ng/mL) or during endogenous t-PA release stimulated by intra-arterial bradykinin infusion in the presence or absence of oral enalapril. Recombinant t-PA caused a dose-dependent reduction in thrombus area under low and high shear conditions (P<0.001 for all). Intra-arterial bradykinin increased plasma t-PA concentrations in the chamber effluent (P<0.01 for all versus saline) that was quadrupled in the presence of enalapril (P<0.0001 versus placebo). These increases were accompanied by an increase in plasma D-dimer concentration (P<0.005 for all versus saline) and, in the presence of enalapril, a reduction in thrombus area in the low shear (16±5; P=0.03) and a trend toward a reduction in the high shear chamber (13±7%; P=0.07). Conclusions—Using a well-characterized clinical model of coronary arterial injury, we demonstrate that endogenous t-PA released from the vascular endothelium enhances fibrinolysis and limits in situ thrombus propagation. These data support a crucial role for the endogenous fibrinolytic system in vivo and suggest that continued exploration and manipulation of its therapeutic potential are warranted.

Currently there is no curative treatment for metastatic clear cell renal cell cancer, the commonest variant of the disease. A key factor in this treatment resistance is thought to be the molecular complexity of the disease. Targeted therapy such as the tyrosine kinase inhibitor (TKI)-sunitinib have been utilized, but only 40% of patients will respond, with the overwhelming majority of these patients relapsing within 1 year. As such the question of intrinsic and acquired resistance in renal cell cancer patients is highly relevant. In order to study resistance to TKIs, with the ultimate goal of developing effective, personalized treatments, sequential tissue after a specific period of targeted therapy is required, an approach which had proved successful in chronic myeloid leukaemia. However the application of such a strategy in renal cell carcinoma is complicated by the high level of both inter- and intratumoral heterogeneity, which is a feature of renal cell carcinoma as well as other solid tumors. Intertumoral heterogeneity due to transcriptomic and genetic differences is well established even in patients with similar presentation, stage and grade of tumor. In addition it is clear that there is great morphological (intratumoral) heterogeneity in RCC, which is likely to represent even greater molecular heterogeneity. Detailed mapping and categorization of RCC tumors by combined morphological analysis and Fuhrman grading allows the selection of representative areas for proteomic analysis. Protein based analysis of RCC is attractive due to its widespread availability in pathology laboratories; however, its application can be problematic due to the limited availability of specific antibodies. Due to the dot blot nature of the Reverse Phase Protein Arrays (RPPA), antibody specificity must be pre-validated; as such strict quality control of antibodies used is of paramount importance. Despite this limitation the dot blot format does allow assay miniaturization, allowing for the printing of hundreds of samples onto a single nitrocellulose slide. Printed slides can then be analyzed in a similar fashion to Western analysis with the use of target specific primary antibodies and fluorescently labelled secondary antibodies, allowing for multiplexing. Differential protein expression across all the samples on a slide can then be analyzed simultaneously by comparing the relative level of fluorescence in a more cost-effective and high-throughput manner.

Although the theoretical possibility of oscillations in MAPK signalling has long been described, experimental validation has proven more elusive. In this study we observed oscillations in MAPK and PI3K signalling in breast cancer cells in response to epidermal growth factor receptor-family stimulation. Using systems level analysis with a kinetic model, we demonstrate that receptor amplification, loss of transcriptional feedback, or pathway crosstalk, are responsible for oscillations in MAPK and PI3K signalling. Transcriptional profiling reveals architectural motifs likely to be responsible for feedback control of oscillations. Overexpression of the HER2 oncogene and inhibition of transcriptional feedback increase the amplitude of oscillations and provide experimental validation of the computational findings.

ABSTRACT Purpose This study aimed to identify predictive proteomic biomarkers of outcome in women with estrogen and/or progesterone receptor-positive (ER/PR-positive) breast cancer after adjuvant tamoxifen, with sufficient power to alter patient management. Methods Using reverse phase protein arrays (RPPA), 140 antibodies were applied to a training set of 197 ER/PR-positive breast cancers to identify predictors. An algorithm was developed that predicted patient outcomes using a subset of antibodies. Since RPPA is a useful exploratory tool but does not lend itself as a practical clinical tool to assay validated biomarkers, quantitative immunofluorescence for selected proteins was applied to 313 ER/PR-positive breast cancers (test set) for validation. Seventy-seven other ER/PR-positive cancers with transcriptional profiling data were used to compare the performance of the proteomic biomarkers and established genomic predictors. All patients were treated with adjuvant tamoxifen after loco-regional therapy. Results Two different combinations (4-protein/3-protein models) of four proteins (CCNB1/PAI1/PR/BCL2), subdivided lymph node-negative breast cancer patients into low-, medium- and high-risk groups with significantly different 10-year recurrence-free survival. The proteomic markers predicted 10-year distant metastasis-free survival in lymph node-negative patients in the test set in the low-, medium- and high-risk groups as follows: 0.9, 0.8, 0.7 (4-protein model (p = 0.05)), 0.91, 0.8, 0.74 (3-protein model (p = 0.004)), with 74%/64% patients in the low-risk groups, respectively. The proteomic models outperformed clinical variables and genomic predictors in multivariate analyses. Conclusion This study validates proteomic biomarkers that can be assayed in a practical inexpensive manner using immunofluorescence to identify lymph node-negative ER/PR-positive patients with excellent outcomes after adjuvant tamoxifen. Disclosure All authors have declared no conflicts of interest.

BACKGROUND:Epithelial-to-mesenchymal transition (EMT) has recently been implicated in the initiation and progression of renal cell carcinoma (RCC). Some mRNA gene expression studies have suggested a link between the EMT phenotype and poorer clinical outcome from RCC. This study evaluated expression of EMT-associated proteins in RCC using in situ automated quantitative analysis immunofluorescence (AQUA) and compared expression levels with clinical outcome.METHODS/PRINCIPAL FINDINGS:Unsupervised hierarchical cluster analysis of pre-existing RCC gene expression array data (GSE16449) from 36 patients revealed the presence of an EMT transcriptional signature in RCC [E-cadherin high/SLUG low/SNAIL low]. As automated immunofluorescence technology is dependent on accurate definition of the tumour cells in which measurements take place is critical, extensive optimisation was carried out resulting in a novel pan-cadherin based tumour mask that distinguishes renal cancer cells from stromal components. 61 patients with ccRCC and clinical follow-up were subsequently assessed for expression of EMT-associated proteins (WT1, SNAIL, SLUG, E-cadherin and phospho-β-catenin) on tissue microarrays. Using Kaplan-Meier analysis both SLUG (p = 0.029) and SNAIL (p = 0.024) (log rank Mantel-Cox) were significantly associated with prolonged progression free survival (PFS). Using Cox regression univariate and multivariate analysis none of the biomarkers were significantly correlated with outcome. 14 of the 61 patients expressed the gene expression analysis predicted EMT-protein signature [E-cadherin high/SLUG low/SNAIL low], which was not found to be associated to PFS when measured at the protein level. A combination of high expression of SNAIL and low stage was able to stratify patients with greater significance (p = 0.001) then either variable alone (high SNAIL p = 0.024, low stage p = 0.029).CONCLUSIONS:AQUA has been shown to have the potential to identify EMT related protein targets in RCC allowing for stratification of patients into high and low risk groups, as well the ability to assess the association of reputed EMT signatures to progression of the disease.