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Biomarkers lie at the heart of precision medicine. Surprisingly, while rapid genomic profiling is becoming ubiquitous, the development of biomarkers usually involves the application of bespoke techniques that cannot be directly applied to other datasets. There is an urgent need for a systematic methodology to create biologically-interpretable molecular models that robustly predict key phenotypes. Here we present SIMMS (Subnetwork Integration for Multi-Modal Signatures): an algorithm that fragments pathways into functional modules and uses these to predict phenotypes. We apply SIMMS to multiple data types across five diseases, and in each it reproducibly identifies known and novel subtypes, and makes superior predictions to the best bespoke approaches. To demonstrate its ability on a new dataset, we profile 33 genes/nodes of the PI3K pathway in 1734 FFPE breast tumors and create a four-subnetwork prediction model. This model out-performs a clinically-validated molecular test in an independent cohort of 1742 patients. SIMMS is generic and enables systematic data integration for robust biomarker discovery.

Background: Aromatase inhibitors improve disease-free survival compared with tamoxifen in postmenopausal women with hormone receptor-positive breast cancer. The Tamoxifen and Exemestane Adjuvant Multinational (TEAM) trial compared exemestane monotherapy with sequential therapy of tamoxifen followed by exemestane. The trial failed to show a statistically significant difference between treatment arms. A robust translational program was established to investigate predictive biomarkers., Methods: A tissue microarray was retrospectively constructed using a subset of patient tissues (n = 4631) from the TEAM trial (n = 9766). Immunohistochemistry was performed for biomarkers, classed into three groups: MAPK pathway, NF-kappa B pathway, and estrogen receptor (ER) phosphorylation. Expression was analyzed for association with relapse-free survival (RFS) at 2.5 and 10 years and treatment regimen using Kaplan-Meier curves and log-rank analysis. All statistical tests were two-sided., Results: In univariate analysis, ER167 (hazard ratio [HR] = 0.71, 95% confidence interval [CI] = 0.59 to 0.85, P < .001), IKKα (HR = 0.74, 95% CI = 0.60 to 0.92, P = .005), Raf-1338 (HR = 0.64, 95% CI = 0.52 to 0.80, P < .001), and p44/42 MAPK202/204 (HR = 0.77, 95% CI = 0.64 to 0.92, P = .004) were statistically significantly associated with improved RFS at 10 years in patients receiving sequential therapy. Associations were strengthened when IKKα, Raf-1338, and ER167 were combined into a cumulative prognostic score (HR = 0.64, 95% CI = 0.52 to 0.77, P < .001). Patients with an all negative IKKα, Raf-1338, and ER167 score favored exemestane monotherapy (odds ratio = 0.56, 95% CI = 0.35 to 0.90). In multivariable analysis, the IKKα, Raf-1338, and ER167 score (P = .001) was an independent prognostic factor for RFS at 10 years in patients receiving sequential therapy., Conclusions: The IKKα, Raf-1338, and ER167 score is an independent predictive biomarker for lower recurrence on sequential therapy. Negative expression may further offer predictive value for exemestane monotherapy.

Context: Hormone receptors HER2/neu and Ki-67 are markers of residual risk in early breast cancer. An algorithm (IHC4) combining these markers may provide additional information on residual risk of recurrence in patients treated with hormone therapy., Objective: To independently validate the IHC4 algorithm in the multinational Tamoxifen Versus Exemestane Adjuvant Multicenter Trial (TEAM) cohort, originally developed on the trans-ATAC (Arimidex, Tamoxifen, Alone or in Combination Trial) cohort, by comparing 2 methodologies., Design: The IHC4 biomarker expression was quantified on TEAM cohort samples (n = 2919) by using 2 independent methodologies (conventional 3,3'-diaminobezidine [DAB] immunohistochemistry with image analysis and standardized quantitative immunofluorescence [QIF] by AQUA technology). The IHC4 scores were calculated by using the same previously established coefficients and then compared with recurrence-free and distant recurrence-free survival, using multivariate Cox proportional hazards modeling., Results: The QIF model was highly significant for prediction of residual risk (P < .001), with continuous model scores showing a hazard ratio (HR) of 1.012 (95% confidence interval [95% CI]: 1.010-1.014), which was significantly higher than that for the DAB model (HR: 1.008, 95% CI: 1.006-1.009); P < .001). Each model added significant prognostic value in addition to recognized clinical prognostic factors, including nodal status, in multivariate analyses. Quantitative immunofluorescence, however, showed more accuracy with respect to overall residual risk assessment than the DAB model., Conclusions: The use of the IHC4 algorithm was validated on the TEAM trial for predicting residual risk in patients with breast cancer. These data support the use of the IHC4 algorithm clinically, but quantitative and standardized approaches need to be used.

Purpose: Deregulation of key PI3K/AKT pathway genes may contribute to endocrine resistance in breast cancer (BC). PIK3CA is the most frequently mutated gene in luminal BC (35%); however, the effect of mutations in helical versus kinase domains remains controversial. We hypothesize that improved outcomes occur in patients with estrogen receptor–positive (ER positive) BC receiving endocrine therapy and possessing PIK3CA mutations., Materials and Methods: DNA was extracted from 4,540 formalin-fixed paraffin-embedded BC samples from the Exemestane Versus Tamoxifen-Exemestane pathology study. Mutational analyses were performed for 25 mutations (PIK3CAx10, AKT1x1, KRASx5, HRASx3, NRASx2 and BRAFx4)., Results: PIK3CA mutations were frequent (39.8%), whereas RAS/RAF mutations were rare (1%). In univariable analyses PIK3CA mutations were associated with significantly improved 5-year distant relapse-free survival (DRFS; HR, 0.76; 95% CI, 0.63 to 0.91; P = .003). However, a multivariable analysis correcting for known clinical and biologic prognostic factors failed to demonstrate that PIK3CA mutation status is an independent prognostic marker for DRFS (HR, 0.92; 95% CI, 0.75 to 1.12; P = .4012). PIK3CA mutations were more frequent in low-risk luminal BCs (e.g., grade 1 nodev 3, node-negative v -positive), confounding the relationship between mutations and outcome., Conclusion: PIK3CA mutations are present in approximately 40% of luminal BCs but are not an independent predictor of outcome in the context of endocrine therapy, whereas RAS/RAF mutations are rare inluminal BC. A complex relationship between low-risk cancers and PIK3CA mutations was identified. Although the PI3K/AKT pathway remains a viable therapeutic target as the result of ahigh mutation frequency, PIK3CA mutations do not seem to affect residual risk following treatment with endocrine therapy.

Purpose: The Tamoxifen and Exemestane Adjuvant Multinational (TEAM) trial included a prospectively planned pathology substudy testing the predictive value of progesterone receptor (PgR) expression for outcome of estrogen receptor-positive (ER-positive) early breast cancer treated with exemestane versus tamoxifen., Patients and Methods: Pathology blocks from 4,781 TEAM patients randomly assigned to exemestane versus tamoxifen followed by exemestane for 5 years of total therapy were collected centrally, and tissue microarrays were constructed from samples from 4,598 patients. Quantitative analysis of hormone receptors (ER and PgR) was performed by using image analysis and immunohistochemistry, and the results were linked to outcome data from the main TEAM trial and analyzed relative to disease-free survival and treatment., Results: Of 4,325 eligible ER-positive patients, 23% were PgR-poor (Allred < 4) and 77% were PgR- rich (Allred ≥ 5). No treatment-by-marker effect for PgR was observed for exemestane versus tamoxifen (PgR-rich hazard ratio [HR], 0.83; 95% CI, 0.65 to 1.05; PgR-poor HR, 0.85; 95% CI, 0.61 to 1.19; P = .88 for interaction). Both PgR and ER expression were associated with patient prognosis in univariate (PgR HR, 0.53; 95% CI, 0.43 to 0.65; P < .001; ER HR, 0.66; 95% CI, 0.51 to 0.86; P = .002), and multivariate analyses (P < .001 and P = .001, respectively). A trend toward a treatment-by-marker effect for ER-rich patients was observed., Conclusion: Preferential exemestane versus tamoxifen treatment benefit was not predicted by PgR expression; conversely, patients with ER-rich tumors may derive additional benefit from exemestane. Quantitative analysis of ER and PgR expression provides highly significant information on risk of early relapse (within 1 to 3 years) during treatment.

A case-control study was performed in order to determine whether expression of the progesterone receptor (PR) and/or aberrations of the PR gene contribute to the development of recurrent endometrial carcinoma. Primary tumours from 44 patients with recurrence of stage I endometrial carcinoma (patients) within 3 years after initial treatment were compared with tumours from 44 matched patients who were free of recurrence for a minimum of 3 years (controls). Paraffin wax-embedded primary tumours (n = 88) and recurrent tumours (n = 32) were analysed immunohistochemically for PR expression. A staining index (SI = 0-9) based on the staining intensity and the number of stained cells was calculated. DNA extracted from paraffin wax-embedded tissues was subjected to PCR-restriction fragment length polymorphism analysis (PCR-RFLP) for determination of the PROGINS DNA sequence alterations and the +331G/A-promoter polymorphism. Low PR expression (SI < 1.0) was observed in 7% of primary tumours derived from controls, 25% of primary tumours from patients with recurrence, and 38% of recurrent tumours. The expression of PR was significantly lower in primary tumours from patients with recurrence (SI = 4.0 +/- 0.5) than in the tumours in the control group (SI = 5.6 +/- 0.5) (T-test for paired analysis, p < 0.05). The PROGINS and +331G/A-promoter polymorphism were not related to age at diagnosis, tumour grade or myometrial invasion. The +331G/A-promoter polymorphism was present in 14% of primary tumours from patients without recurrence, compared with 17% of patients with recurrence. The PROGINS polymorphism was observed in 16% of primary tumours from patients without, and in 34% of patients with, recurrence (OR 2.6; 95% CI: 0.9-7.6). Most interestingly, patients who carried the PROGINS variant and in whom a PR-expressing tumour was diagnosed were at significantly enhanced risk of relapse (OR 4.7; 95% CI: 1.3-17.1). In conclusion, low PR expression tended to be associated with recurrent disease, and PR expression in tumours from patients carrying the PROGINS allele was predictive of the risk of recurrence.

Adrenomedullin (ADM) is an angiogenic factor that has also been shown to be a mitogen and a hypoxia survival factor for tumour cells. These properties point to ADM as a potential promoter of human malignancies, but little data are available concerning the expression of ADM in human breast cancer. In the present work, we have examined ADM peptide expression in a series of malignant breast tumours by immunohistochemistry using a newly developed anti-ADM monoclonal antibody. In addition, ADM plasma concentrations in breast cancer patients and healthy controls were determined by radioimmunoassay. Of the examined breast cancer samples, 27/33 (82%) showed a moderate to strong staining intensity. ADM-peptide expression in breast tumours was significantly correlated with axillary lymph node metastasis (P=0.030). Analysis of ADM plasma concentrations showed no significant difference between the circulating ADM levels of breast cancer patients and healthy controls. However, a significant positive correlation was found between tumour size and plasma ADM levels (r=0.641, P=0.017). Moreover, ADM levels in breast cancer patients correlated with the presence of lymph node metastasis (P=0.002). In conclusion, we have shown for the first time that ADM peptide is widely expressed in breast cancer and that the degree of expression is associated with lymph node metastasis. ADM peptide in plasma of breast cancer patients reflects the size of the primary tumour, but is unlikely to be a useful tumour marker for the detection of breast cancer. Plasma ADM might represent an independent predictor of lymph node metastasis. The clinical implications of these findings remain to be evaluated.

Background: Axillary lymph node metastases in breast cancer patients are one of the most important prognostic factors. Many previous studies have shown that in the detection of occult micrometastases immunohistochemical methods are superior when compared to routine hematoxylin-eosin staining. The aim of the study was to document the rate of missed occult micrometastases on routine hematoxylin-eosin staining in our department, in a retrospective study., Patients and Methods: One hundred and one tumors of patients with breast cancer were included in this study. Immunohistochemical staining was performed using Pan-Cytokeratin AE1/AE3 antibody. The number of nodes examined was 1301 (mean per patient: 12.9; range: one to 26)., Results: Of the 101 tumors studied, eleven had occult lymph node metastases detected by immunohistochemical methods. After repeated review by two independent pathologists, in two out of eleven patients lymph node metastases were confirmed even on hematoxylin-eosin staining. In nine out of eleven patients hematoxylin-eosin staining was not sufficient to detect occult micrometastases., Conclusion: Immunohistochemical methods enhance the detection rate of occult micrometastases in axillary lymph nodes of breast cancer patients and are recommended for routine diagnostic use in patients who have been diagnosed node-negative on routine hematoxylin-eosin staining.

Conventional cytosol estrogen receptor analysis is not a significant prognostic variable in serous ovarian carcinoma. Although the use of immunocytochemical receptor analysis for estrogen does provide prognostically useful information in enhanced accuracy of predicting survival in patients with ovarian cancer, its usefulness can still be improved. Surgical samples from ovarian carcinomas are heterogeneous in tissue composition. Immunocytochemical receptor analysis allows for the specific assessment of the tumorous portions of a histological specimen. However, it is limited by its dependence on staining intensity as the determining factor. Biochemical receptor analysis does provide objective information concerning the number of receptor molecules present in a given sample, but the value is not adjusted for histological composition of the tumor section. Therefore, we have attempted to combine the advantages of both methods. By adjusting the conventional receptor analysis for the percentage of tumor present in the specimen, we have eliminated the tissue heterogeneity as a confounding variable. The resulting value is named Composition Adjusted Receptor Level or CARL. A prospective study was performed on the estrogen receptor concentrations in 61 ovarian cancers. Minimum follow-up was 8 years. For the percentage of tumor in the specimen, a highly significant correlation of the assessment of the two pathologists was observed. Stage (P < 0.05) and grade (P < 0.05) as well as cell type (P < 0.05) were found to be significant prognostic variables. In an attempt to eliminate the confounding influences of these variables, the CARL of the estrogen receptor was assessed with regard to its prognostic significance in 32 grade 2 and 3 serous carcinomas of the ovary, stage III and IV. A linear correlation between CARL and survival was found above a threshold estrogen receptor concentration of 15 fmol/mg cytosol protein using a correlation of the Cox proportional hazards model (P < 0.02). Our data suggest that (a) the assessment of the percentage of tumor in a given sample is not significantly observer dependent, (b) CARL is a significant predictor of survival in serous ovarian carcinoma, and (c) a CARL should be determined for the analysis of any cytosol receptor in solid tumors.