Pathway-specific therapy is the future of cancer management. The oncogenic phosphatidylinositol 3-kinase (PI3K) pathway is frequently activated in solid tumors; however, currently, no reliable test for PI3K pathway activation exists for human tumors. Taking advantage of the observation that loss of PTEN, the negative regulator of PI3K, results in robust activation of this pathway, we developed and validated a microarray gene expression signature for immunohistochemistry (IHC)-detectable PTEN loss in breast cancer (BC). The most significant signature gene was PTEN itself, indicating that PTEN mRNA levels are the primary determinant of PTEN protein levels in BC. Some PTEN IHC-positive BCs exhibited the signature of PTEN loss, which was associated to moderately reduced PTEN mRNA levels cooperating with specific types of PIK3CA mutations and/or amplification of HER2. This demonstrates that the signature is more sensitive than PTEN IHC for identifying tumors with pathway activation. In independent data sets of breast, prostate, and bladder carcinoma, prediction of pathway activity by the signature correlated significantly to poor patient outcome. Stathmin, encoded by the signature gene STMN1, was an accurate IHC marker of the signature and had prognostic significance in BC. Stathmin was also pathway-pharmacodynamic in vitro and in vivo. Thus, the signature or its components such as stathmin may be clinically useful tests for stratification of patients for anti-PI3K pathway therapy and monitoring therapeutic efficacy. This study indicates that aberrant PI3K pathway signaling is strongly associated with metastasis and poor survival across carcinoma types, highlighting the enormous potential impact on patient survival that pathway inhibition could achieve.breast cancer ͉ metastasis ͉ stathmin ͉ microarray

Background: Soft tissue sarcoma (STS) diagnosis is challenging because of a multitude of histopathological subtypes, different genetic characteristics, and frequent intratumoral pleomorphism. One-third of STS metastasize and current risk-stratification is suboptimal, therefore, novel diagnostic and prognostic markers would be clinically valuable. We assessed the diagnostic and prognostic value of array-based gene expression profiles using 27 k cDNA microarrays in 177, mainly high-grade, STS of 13 histopathological subtypes.

BackgroundPresence of circulating tumor cells (CTCs) is a validated prognostic marker in metastatic breast cancer. Additional prognostic information may be obtained by morphologic characterization of CTCs. We explored whether apoptotic CTCs, CTC clusters and leukocytes attached to CTCs are associated with breast cancer subtype and prognosis at base-line (BL) and in follow-up (FU) blood samples in patients with metastatic breast cancer scheduled for first-line systemic treatment.MethodsPatients with a first metastatic breast cancer event were enrolled in a prospective observational study prior to therapy initiation and the CellSearch system (Janssen Diagnostics) was used for CTC enumeration and characterization. We enrolled patients (N = 52) with ≥5 CTC/7.5 ml blood at BL (median 45, range 5–668) and followed them with blood sampling for 6 months during therapy. CTCs were evaluated for apoptotic changes, CTC clusters (≥3 nuclei), and leukocytes associated with CTC (WBC-CTC, ≥1 CTC + ≥1 leukocytes) at all time-points by visual examination of the galleries generated by the CellTracks Analyzer.ResultsAt BL, patients with triple-negative and HER2-positive breast cancer had blood CTC clusters present more frequently than patients with hormone receptor-positive cancer (P = 0.010). No morphologic characteristics were associated with prognosis at BL, whereas patients with apoptotic CTCs or clusters in FU samples had worse prognosis compared to patients without these characteristics with respect to progression-free (PFS) and overall survival (OS) (log-rank test: P = 0.0012 or lower). Patients with apoptotic or clustered CTCs at any time-point had impaired prognosis in multivariable analyses adjusting for number of CTCs and other prognostic factors (apoptosis: HROS = 25, P < 0.001; cluster: HROS = 7.0, P = 0.006). The presence of WBC-CTCs was significantly associated with an inferior prognosis in terms of OS at 6 months in multivariable analysis.ConclusionsPatients with a continuous presence of apoptotic or clustered CTCs in FU samples after systemic therapy initiation had worse prognosis than patients without these CTC characteristics. In patients with ≥5 CTC/7.5 ml blood at BL, morphologic characterization of persistent CTCs could be an important prognostic marker during treatment, in addition to CTC enumeration alone.Clinical Trials (NCT01322893), registration date 21 March 2011Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-016-2406-y) contains supplementary material, which is available to authorized users.

Cyclins D1 and A2 are cell cycle regulators that also have the ability to interact with the estrogen receptor (ER) and consequently interfere with antiestrogen treatment in breast cancer. Experimental data support this concept, but the clinical relevance needs to be further established. In this study, we evaluated cyclin D1 and A2 protein expression by immunohistochemistry and cyclin D1 gene (CCND1) amplification by fluorescence in situ hybridization in 500 primary breast cancers arranged in tissue microarrays. Patients had been randomized to 2 years of adjuvant tamoxifen or no treatment with a median follow-up of 14 years, allowing for subgroup analysis of treatment response defined by cyclin status. We found that both cyclin D1 and A2 protein overexpression was associated with an impaired tamoxifen response, although not significant in multivariate interaction analyses, whereas tamoxifen-treated patients with CCND1-amplified tumors had a substantially increased risk for disease recurrence after tamoxifen treatment in univariate analyses [relative risk (RR), 2.22; 95% confidence interval (95% CI), 0.94-5.26; P = 0.06] in contrast to nonamplified tumors (RR, 0.39; 95% CI, 0.23-0.65; P < 0.0001). Consequently, a highly significant interaction between tamoxifen treatment and CCND1 amplification could be shown regarding both recurrence-free survival (RR, 6.38; 95% CI, 2.29-17.78; P < 0.001) and overall survival (RR, 5.34; 95% CI, 1.84-15.51; P = 0.002), suggesting an agonistic effect of tamoxifen in ERpositive tumors. In node-positive patients, the disparate outcome according to gene amplification status was even more accentuated. In summary, our data implicate that despite a significant correlation to cyclin D1 protein expression, amplification status of the CCND1 gene seems a strong independent predictor of tamoxifen response, and possibly agonism, in premenopausal breast cancer. (Cancer Res 2005; 65(17): 8009-16)

Background Sentinel lymph node biopsy (SLNB) is standard staging procedure for nodal status in breast cancer, but lacks therapeutic benefit for patients with benign sentinel nodes. For patients with positive sentinel nodes, individualized surgical strategies are applied depending on the extent of nodal involvement. Preoperative prediction of nodal status is thus important for individualizing axillary surgery avoiding unnecessary surgery. We aimed to predict nodal status in clinically node-negative breast cancer and identify candidates for SLNB omission by including patient-related and pathological characteristics into artificial neural network (ANN) models. Methods Patients with primary breast cancer were consecutively included between January 1, 2009 and December 31, 2012 in a prospectively maintained pathology database. Clinical- and radiological data were extracted from patient’s files and only clinically node-negative patients constituted the final study cohort. ANN-based models for nodal prediction were constructed including 15 risk variables for nodal status. Area under the receiver operating characteristic curve (AUC) and Hosmer-Lemeshow goodness-of-fit test (HL) were used to assess performance and calibration of three predictive ANN-based models for no lymph node metastasis (N0), metastases in 1–3 lymph nodes (N1) and metastases in ≥ 4 lymph nodes (N2). Linear regression models for nodal prediction were calculated for comparison. Results Eight hundred patients (N0, n = 514; N1, n = 232; N2, n = 54) were included. Internally validated AUCs for N0 versus N+ was 0.740 (95% CI = 0.723–0.758); median HL was 9.869 ( P = 0.274), for N1 versus N0, 0.705 (95% CI = 0.686–0.724; median HL: 7.421; P = 0.492) and for N2 versus N0 and N1, 0.747 (95% CI = 0.728–0.765; median HL: 9.220; P = 0.324). Tumor size and vascular invasion were top-ranked predictors of all three end-points, followed by estrogen receptor status and lobular cancer for prediction of N2. For each end-point, ANN models showed better discriminatory performance than multivariable logistic regression models. Accepting a false negative rate (FNR) of 10% for predicting N0 by the ANN model, SLNB could have been abstained in 27.25% of patients with clinically node-negative axilla. Conclusions In this retrospective study, ANN showed promising result as decision-supporting tools for estimating nodal disease. If prospectively validated, patients least likely to have nodal metastasis could be spared SLNB using predictive models. Trial registration Registered in the ISRCTN registry with study ID ISRCTN14341750 . Date of registration 23/11/2018. Retrospectively registered. Electronic supplementary material T...