Increasing knowledge about signal transduction pathways as drivers of cancer growth has elicited the development of "targeted drugs," which inhibit aberrant signaling pathways. They require a companion diagnostic test that identifies the tumor-driving pathway; however, currently available tests like estrogen receptor (ER) protein expression for hormonal treatment of breast cancer do not reliably predict therapy response, at least in part because they do not adequately assess functional pathway activity. We describe a novel approach to predict signaling pathway activity based on knowledge-based Bayesian computational models, which interpret quantitative transcriptome data as the functional output of an active signaling pathway, by using expression levels of transcriptional target genes. Following calibration on only a small number of cell lines or cohorts of patient data, they provide a reliable assessment of signaling pathway activity in tumors of different tissue origin. As proof of principle, models for the canonical Wnt and ER pathways are presented, including initial clinical validation on independent datasets from various cancer types. Cancer Res; 74(11); 2936-45. Ó2014 AACR.

Signal transduction pathways are important in physiology and pathophysiology. Targeted drugs aim at modifying pathogenic pathway activity, e.g., in cancer. Optimal treatment choice requires assays to measure pathway activity in individual patient tissue or cell samples. We developed a method enabling quantitative measurement of functional pathway activity based on Bayesian computational model inference of pathway activity from measurements of mRNA levels of target genes of the pathway-associated transcription factor. Oestrogen receptor, Wnt, and PI3K-FOXO pathway assays have been described previously. Here, we report model development for androgen receptor, Hedgehog, TGFβ, and NFκB pathway assays, biological validation on multiple cell types, and analysis of data from published clinical studies (multiple sclerosis, amyotrophic lateral sclerosis, contact dermatitis, Ewing sarcoma, lymphoma, medulloblastoma, ependymoma, skin and prostate cancer). Multiple pathway analysis of clinical prostate cancer (PCa) studies showed increased AR activity in hyperplasia and primary PCa but variable AR activity in castrate resistant (CR) PCa, loss of TGFβ activity in PCa, increased Wnt activity in TMPRSS2:ERG fusion protein-positive PCa, active PI3K pathway in advanced PCa, and active PI3K and NFκB as potential hormonal resistance pathways. Potential value for future clinical practice includes disease subtyping and prediction and targeted therapy response prediction and monitoring.

Endocrine therapy is important for management of patients with estrogen receptor (ER)-positive breast cancer; however, positive ER staining does not reliably predict therapy response. We assessed the potential to improve prediction of response to endocrine treatment of a novel test that quantifies functional ER pathway activity from mRNA levels of ER pathway-specific target genes. ER pathway activity was assessed on datasets from three neoadjuvant-treated ER-positive breast cancer patient cohorts: Edinburgh: 3-month letrozole, 55 pre-/2-week/posttreatment matched samples; TEAM IIa: 3-to 6-month exemestane, 49 pre-/28 posttreatment paired samples; and NEWEST: 16-week fulvestrant, 39 pretreatment samples. ER target gene mRNA levels were measured in fresh-frozen tissue (Edinburgh, NEWEST) with Affymetrix microarrays, and in formalin-fixed paraffin-embedded samples (TEAM IIa) with qRT-PCR. Approximately one third of ER-positive patients had a functionally inactive ER pathway activity score (ERPAS), which was associated with a nonresponding status. Quantitative ERPAS decreased significantly upon therapy (P < 0.001 Edinburgh and TEAM IIa). Responders had a higher pretreatment ERPAS and a larger 2-week decrease in activity (P ¼ 0.02 Edinburgh). Progressive disease was associated with low baseline ERPAS (P ¼ 0.03 TEAM IIa; P ¼ 0.02 NEWEST), which did not decrease further during treatment (P ¼ 0.003 TEAM IIa). In contrast, the staining-based ER Allred score was not significantly associated with therapy response (P ¼ 0.2). The ERPAS identified a subgroup of ER-positive patients with a functionally inactive ER pathway associated with primary endocrine resistance. Results confirm the potential of measuring functional ER pathway activity to improve prediction of response and resistance to endocrine therapy.

In this report, we studied the potential of a novel biomarker to predict outcomes of a cohort of prostate cancer patients who underwent surgery more than 10 yr ago. We found that a gene called phosphodiesterase-4D7 added extra information to the available clinical data. We conclude that the measurement of this gene in tumor tissue may contribute to more effective treatment decisions.

Previously, a pulse wave propagation model was developed that has potential in supporting decision-making in arteriovenous fistula (AVF) surgery for hemodialysis. To adapt the wave propagation model to personalized conditions, patient-specific input parameters should be available. In clinics, the number of measurable input parameters is limited which results in sparse datasets. In addition, patient data are compromised with uncertainty. These uncertain and incomplete input datasets will result in model output uncertainties. By means of a sensitivity analysis the propagation of input uncertainties into output uncertainty can be studied which can give directions for input measurement improvement. In this study, a computational framework has been developed to perform such a sensitivity analysis with a variance-based method and Monte Carlo simulations. The framework was used to determine the influential parameters of our pulse wave propagation model applied to AVF surgery, with respect to parameter prioritization and parameter fixing. With this we were able to determine the model parameters that have the largest influence on the predicted mean brachial flow and systolic radial artery pressure after AVF surgery. Of all 73 parameters 51 could be fixed within their measurement uncertainty interval without significantly influencing the output, while 16 parameters importantly influence the output uncertainty. Measurement accuracy improvement should thus focus on these 16 influential parameters. The most rewarding are measurement improvements of the following parameters: the mean aortic flow, the aortic windkessel resistance, the parameters associated with the smallest arterial or venous diameters of the AVF in- and outflow tract and the radial artery windkessel compliance.

Estrogen receptor positive (ER+) breast cancer patients are eligible for hormonal treatment, but only around half respond. A test with higher specificity for prediction of endocrine therapy response is needed to avoid hormonal overtreatment and to enable selection of alternative treatments. A novel testing method was reported before that enables measurement of functional signal transduction pathway activity in individual cancer tissue samples, using mRNA levels of target genes of the respective pathway-specific transcription factor. Using this method, 130 primary breast cancer samples were analyzed from non-metastatic ER+ patients, treated with surgery without adjuvant hormonal therapy, who subsequently developed metastatic disease that was treated with first-line tamoxifen. Quantitative activity levels were measured of androgen and estrogen receptor (AR and ER), PI3K-FOXO, Hedgehog (HH), NFκB, TGFβ, and Wnt pathways. Based on samples with known pathway activity, thresholds were set to distinguish low from high activity. Subsequently, pathway activity levels were correlated with the tamoxifen treatment response and progression-free survival. High ER pathway activity was measured in 41% of the primary tumors and was associated with longer time to progression (PFS) of metastases during first-line tamoxifen treatment. In contrast, high PI3K, HH, and androgen receptor pathway activity was associated with shorter PFS, and high PI3K and TGFβ pathway activity with worse treatment response. Potential clinical utility of assessment of ER pathway activity lies in predicting response to hormonal therapy, while activity of PI3K, HH, TGFβ, and AR pathways may indicate failure to respond, but also opens new avenues for alternative or complementary targeted treatments.

BACKGROUND: Approximately 20% of women with endometrial cancer have advanced-stage disease or suffer from a recurrence. For these women, prognosis is poor, and palliative treatment options include hormonal therapy and chemotherapy. Lack of predictive biomarkers and suboptimal use of existing markers for response to hormonal therapy have resulted in overall limited efficacy. OBJECTIVE: This study aimed to improve the efficacy of hormonal therapy by relating immunohistochemical expression of estrogen and progesterone receptors and estrogen receptor pathway activity scores to response to hormonal therapy. STUDY DESIGN: Patients with advanced or recurrent endometrial cancer and available biopsies taken before the start of hormonal therapy were identified in 16 centers within the European Network for Individualized Treatment in Endometrial Cancer and the Dutch Gynecologic Oncology Group. Tumor tissue was analyzed for estrogen and progesterone receptor expressions and estrogen receptor pathway activity using a quantitative polymerase chain reactionebased messenger RNA model to measure the activity of estrogen receptorerelated target genes in tumor RNA. The primary endpoint was response rate defined as complete and partial response using the Response Evaluation Criteria in Solid Tumors. The secondary endpoints were clinical benefit rate and progression-free survival. RESULTS: Pretreatment biopsies with sufficient endometrial cancer tissue and complete response evaluation were available in 81 of 105 eligible cases. Here, 22 of 81 patients (27.2%) with a response had estrogen and progesterone receptor expressions of >50%, resulting in a response rate of 32.3% (95% confidence interval, 20.9e43.7) for an estrogen receptor expression of >50% and 50.0% (95% confidence interval, 35.2e64.8) for a progesterone receptor expression of >50%. Clinical benefit rate was 56.9% for an estrogen receptor expression of >50% (95% confidence interval, 44.9e68.9) and 75.0% (95% confidence interval, 62.2e87.8) for a progesterone receptor expression of >50%. The application of the estrogen receptor pathway test to cases with a progesterone receptor expression of >50% resulted in a response rate of 57.6% (95% confidence interval, 42.1e73.1). After 2 years of follow-up, 34.3% of cases (95% confidence interval, 20e48) with a progesterone receptor expression of >50% and 35.8% of cases (95% confidence interval, 20e52) with an estrogen receptor pathway activity score of >15 had not progressed. CONCLUSION: The prediction of response to hormonal treatment in endometrial cancer improves substantially with a 50% cutoff level for progesterone receptor immunohistochemical expression and by applying a sequential test algorithm using progesterone receptor immunohistochemical expression and estrogen receptor pathway activity scores. However, results need to be validated in the prospective Prediction of Response to Hormonal Therapy in Advanced and Recurrent Endometrial Cancer (PROMOTE) study.

Background Oestrogen receptor (ER) expression is a prognostic biomarker in endometrial cancer (EC). However, expression does not provide information about the functional activity of the ER pathway. We evaluated a model to quantify ER pathway activity in EC, and determined the prognostic relevance of ER pathway activity. Methods ER pathway activity was measured in two publicly available datasets with endometrial and EC tissue, and one clinical cohort with 107 samples from proliferative and hyperplastic endometrium and endometrioid-type EC (EEC) and uterine serous cancer (USC). ER pathway activity scores were inferred from ER target gene mRNA levels from Affymetrix microarray data (public datasets), or measured by qPCR on formalin-fixed paraffin-embedded samples (clinical cohort) and related to ER expression and outcome. Results ER pathway activity scores differed significantly throughout the menstrual cycle supporting the validity of the pathway test. The highest ER pathway scores were found in proliferative and hyperplastic endometrium and stage I EEC, whereas stage II–IV EEC and USCs had significantly lower levels. Low ER pathway activity was associated with recurrent disease, and added prognostic value in patients with low ER expression. Conclusion The ER pathway test reflects activity of the ER pathway, and may improve prediction of outcome in EC patients.