Dynamic modulation of phosphoprotein expression in ovarian cancer xenograft models.

BACKGROUND: The dynamic changes that occur in protein expression after treatment of a cancer in vivo are poorly described. In this study we measure the effect of chemotherapy over time on the expression of a panel of proteins in ovarian cancer xenograft models. The objective was to identify phosphoprotein and other protein changes indicative of pathway activation that might link with drug response. METHODS: Two xenograft models, platinum-responsive OV1002 and platinum-unresponsive HOX424, were used. Treatments were carboplatin and carboplatin-paclitaxel. Expression of 49 proteins over 14 days post treatment was measured by quantitative immunofluorescence and analysed by AQUA. RESULTS: Carboplatin treatment in the platinum-sensitive OV1002 model triggered up-regulation of cell cycle, mTOR and DDR pathways, while at late time points WNT, invasion, EMT and MAPK pathways were modulated. Estrogen receptor-alpha (ESR1) and ERBB pathways were down-regulated early, within 24 h from treatment administration. Combined carboplatin-paclitaxel treatment triggered a more extensive response in the OV1002 model modulating expression of 23 of 49 proteins. Therefore the cell cycle and DDR pathways showed similar or more pronounced changes than with carboplatin alone. In addition to expression of pS6 and pERK increasing, components of the AKT pathway were modulated with pAKT increasing while its regulator PTEN was down-regulated early. WNT signaling, EMT and invasion markers were modulated at later time points. Additional pathways were also observed with the NFκB and JAK/STAT pathways being up-regulated. ESR1 was down-regulated as was HER4, while further protein members of the ERBB pathway were upregulated late. By contrast, in the carboplatin-unresponsive HOX 424 xenograft, carboplatin only modulated expression of MLH1 while carboplatin-paclitaxel treatment modulated ESR1 and pMET. CONCLUSIONS: Thirteen proteins were modulated by carboplatin and a more robust set of changes by carboplatin-paclitaxel. Early changes included DDR and cell cycle regulatory proteins associating with tumor volume changes, as expected. Changes in ESR1 and ERBB signaling were also observed. Late changes included components of MAPK signaling, EMT and invasion markers and coincided in time with reversal in tumor volume reduction. These results suggest potential therapeutic roles for inhibitors of such pathways that may prolong chemotherapeutic effects.

Multi-Scale Genomic, Transcriptomic and Proteomic Analysis of Colorectal Cancer Cell Lines to Identify Novel Biomarkers.

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.

Predicting response to the anti-estrogen fulvestrant in recurrent ovarian cancer.

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.

Heterogeneity mapping of protein expression in tumors using quantitative immunofluorescence.

Morphologic heterogeneity within an individual tumor is well-recognized by histopathologists in surgical practice. While this often takes the form of areas of distinct differentiation into recognized histological subtypes, or different pathological grade, often there are more subtle differences in phenotype which defy accurate classification (Figure 1). Ultimately, since morphology is dictated by the underlying molecular phenotype, areas with visible differences are likely to be accompanied by differences in the expression of proteins which orchestrate cellular function and behavior, and therefore, appearance. The significance of visible and invisible (molecular) heterogeneity for prognosis is unknown, but recent evidence suggests that, at least at the genetic level, heterogeneity exists in the primary tumor(1,2), and some of these sub-clones give rise to metastatic (and therefore lethal) disease. Moreover, some proteins are measured as biomarkers because they are the targets of therapy (for instance ER and HER2 for tamoxifen and trastuzumab (Herceptin), respectively). If these proteins show variable expression within a tumor then therapeutic responses may also be variable. The widely used histopathologic scoring schemes for immunohistochemistry either ignore, or numerically homogenize the quantification of protein expression. Similarly, in destructive techniques, where the tumor samples are homogenized (such as gene expression profiling), quantitative information can be elucidated, but spatial information is lost. Genetic heterogeneity mapping approaches in pancreatic cancer have relied either on generation of a single cell suspension(3), or on macrodissection(4). A recent study has used quantum dots in order to map morphologic and molecular heterogeneity in prostate cancer tissue(5), providing proof of principle that morphology and molecular mapping is feasible, but falling short of quantifying the heterogeneity. Since immunohistochemistry is, at best, only semi-quantitative and subject to intra- and inter-observer bias, more sensitive and quantitative methodologies are required in order to accurately map and quantify tissue heterogeneity in situ. We have developed and applied an experimental and statistical methodology in order to systematically quantify the heterogeneity of protein expression in whole tissue sections of tumors, based on the Automated QUantitative Analysis (AQUA) system(6). Tissue sections are labeled with specific antibodies directed against cytokeratins and targets of interest, coupled to fluorophore-labeled secondary antibodies. Slides are imaged using a whole-slide fluorescence scanner. Images are subdivided into hundreds to thousands of tiles, and each tile is then assigned an AQUA score which is a measure of protein concentration within the epithelial (tumor) component of the tissue. Heatmaps are generated to represent tissue expression of the proteins and a heterogeneity score assigned, using a statistical measure of heterogeneity originally used in ecology, based on the Simpson's biodiversity index(7). To date there have been no attempts to systematically map and quantify this variability in tandem with protein expression, in histological preparations. Here, we illustrate the first use of the method applied to ER and HER2 biomarker expression in ovarian cancer. Using this method paves the way for analyzing heterogeneity as an independent variable in studies of biomarker expression in translational studies, in order to establish the significance of heterogeneity in prognosis and prediction of responses to therapy.

Sprouty 2 is an independent prognostic factor in breast cancer and may be useful in stratifying patients for trastuzumab therapy.

BACKGROUND: Resistance to trastuzumab is a clinical problem, partly due to overriding activation of MAPK/PI3K signalling. Sprouty-family proteins are negative regulators of MAPK/PI3K signalling, but their role in HER2-therapy resistance is unknown. PATIENTS AND METHODS: Associations between Sprouty gene expression and clinicopathological features were investigated in a breast cancer microarray meta-analysis. Changes in expression of Spry2 and feedback inhibition on trastuzumab resistance were studied in SKBr3 and BT474 breast carcinoma cell lines using cell viability assays. Spry2 protein expression was measured by quantitative immunofluorescence in a cohort of 122 patients treated with trastuzumab. RESULTS: Low gene expression of Spry2 was associated with increased pathological grade, high HER2 expression, and was a significant independent prognostic factor. Overexpression of Spry2 in SKBr3s resulted in enhanced inhibition of cell viability after trastuzumab treatment, and the PI3K-inhibitor LY294002 had a similar effect. Low Spry2 expression was associated with increased risk of death (HR = 2.28, 95% CI 1.22-4.26; p = 0.008) in trastuzumab-treated patients, including in multivariate analysis. Stratification of trastuzumab-treated patients using PTEN and Spry2 was superior to either marker in isolation. CONCLUSION: In breast cancers with deficient feedback inhibition, combinatorial therapy with negative regulators of growth factor signalling may be an effective therapeutic strategy.

Trastuzumab and pertuzumab produce changes in morphology and estrogen receptor signaling in ovarian cancer xenografts revealing new treatment strategies.

PURPOSE: The aim of this study was to investigate the antitumor effects of HER2-directed combination therapy in ovarian cancer xenograft models to evaluate their potential. The combinations of trastuzumab and pertuzumab, and trastuzumab and aromatase inhibitor therapy were investigated. EXPERIMENTAL DESIGN: The effects of trastuzumab, pertuzumab, and letrozole on growth response, apoptosis, morphology, and gene and protein expression were evaluated in the SKOV3 ovarian cancer cell line xenograft and a panel of five human ovarian xenografts derived directly from clinical specimens. RESULTS: The combination of HER2-directed antibodies showed enhanced antitumor activity compared with single antibody therapy in the SKOV3 xenograft model. Apoptosis, morphology, and estrogen-regulated gene expression were modulated by these antibodies in both spatial and temporal manners. A panel of ovarian cancer xenografts showed differential growth responses to the combination of trastuzumab and pertuzumab. High HER2 expression and increasing HER3 protein expression on treatment were associated with growth response. In trastuzumab-treated SKOV3 tumors, there was a change in tumor morphology, with a reduction in frequency of estrogen receptor alpha (ERα)-negative clear cell areas. Trastuzumab, but not pertuzumab, increased expression of ERα in SKOV3 xenografts when analyzed by quantitative immunofluorescence. ERα and downstream signaling targets were modulated by trastuzumab alone and in combination. Trastuzumab enhanced the responsiveness of SKOV3 xenografts to letrozole when given in combination. CONCLUSIONS: These data suggest that trastuzumab in combination with pertuzumab could be an effective approach in high HER2-expressing ovarian cancers and could also enhance sensitivity to endocrine therapy in ERα-positive ovarian cancer.

Phosphoprotein pathway profiling of ovarian carcinoma for the identification of potential new targets for therapy.

Advances in predicting responses to therapies in ovarian cancer have not matched progress seen in other solid-organ tumours: ovarian cancer remains a poor-prognosis disease. There has been a paradigm shift in molecular therapeutics away from targeting individual molecules to whole biological pathways. The aim of this study was to quantitatively measure the activation state of druggable oncogenic pathways by generating a phosphoprotein profile in cancer tissues, in order to establish associations with clinicopathological parameters and to identify treatment groups for targeted therapy. In total we analysed the expression of ten phosphoproteins within eight signalling pathways (PI3K, MAPK, ß-catenin, STAT, NFκB, ER, cell cycle and DNA damage response), proliferation (phospho-histone H3 and Ki67) and apoptosis (activated caspase 3), in two independent cohorts of ovarian cancers using quantitative immunofluorescence image analysis. Data were analysed by unsupervised and K-means clustering to determine new biologically relevant groups. Expression of markers of the five main pathways deregulated by mutation or copy number changes was different between histological subtypes. Four main clusters with distinct phosphoprotein profiles were identified, which were significantly associated with survival in univariate analysis, and which had distinct patterns of pathway expression reproducible between clinical cohorts. These pathway profiles suggest novel therapeutic regimens for the treatment of ovarian cancer, such as MAPK-inhibition in serous or clear cell carcinomas, or combined inhibition of STAT, NFκB and WNT signalling.