The validated EndoPredict assay is a novel tool to predict the risk of metastases of patients with estrogen receptor positive, HER2 negative breast cancer treated with endocrine therapy alone. It has been designed to integrate genomic and clinical information and includes clinico-pathological factors such as tumor size and nodal status. The test is feasible in a decentral setting in molecular pathology laboratories. In this project, we investigated the performance of this test in clinical practice, and performed a retrospective evaluation of its impact on treatment decisions in breast cancer. During one year, EndoPredict assays from 167 patients could be successfully performed. For retrospective evaluation of treatment decisions, a questionnaire was sent to the clinical partner. Regarding the molecular EP class, samples from 56 patients (33.5%) had a low-risk, whereas 111 patients (66.5%) showed a high-risk gene profile. After integration of the clinicopathological factors the combined clinical and molecular score (EPclin) resulted in a low-risk group of 77 patients (46.4%), while 89 (53.6%) had a high risk EPclin score. The EPclin-based estimated median 10-year-risk for metastases with endocrine therapy alone was 11% for the whole cohort. The median handling time averaged three days (range: 0 to 11 days), 59.3% of the tests could be performed in three or less than three days. Comparison of pre- and post-test therapy decisions showed a change of therapy in 37.7% of patients. 16 patients (12.3%) had a change to an additional chemotherapy while 25.4% of patients (n = 33) changed to an endocrine therapy alone. In 73 patients (56.2%) no change of therapy resulted. In 6.1% of patients (n = 8), the patients did not agree to the recommendation of the tumor board. Our results show that the EndoPredict assay could be routinely performed in decentral molecular pathology laboratories and the results markedly change treatment decisions.
Taxanes are regarded as the most effective single agents in the treatment of metastatic breast cancer (MBC). For conventional taxanes, crucial toxicities and impairments in clinical efficacy are related to solvents necessary because of the agents’ hydrophobicity. The mandatory premedication with corticosteroids causes additional side effects. Nab-paclitaxel is a solvent-free colloidal suspension of paclitaxel and human serum albumin that exploits the physiological transport properties of albumin. It is registered as monotherapy with a recommended dose of 260 mg/m2 every 3 weeks for the treatment of patients with MBC, who have failed a first-line treatment of metastatic disease and for whom a standard anthracycline treatment is not indicated. Clinical evidence is available for the registered 3-weekly administration and for alternative weekly schedules in first and further lines of therapy of patients with MBC. During an advisory board meeting, a group of 8 German breast cancer experts reviewed the clinical data of nab-paclitaxel in MBC and discussed how nab-paclitaxel could be used in clinical practice on the basis of the current data.
First-line therapy; Metastatic breast cancer; Chemotherapy; Weekly; nab-Paclitaxel; Paclitaxel; Docetaxel
There is a lack of psychotherapeutic trials of treatments of comorbid depression in cancer patients. Our study determines the efficacy of a manualized short-term psychodynamic psychotherapy and predictors of outcome by personality and quality of the therapeutic relationship.
Eligible breast cancer patients with comorbid depression are assigned to short-term psychodynamic psychotherapy (up to 20 + 5 sessions) or to treatment as usual (augmented by recommendation for counseling center and physician information). We plan to recruit a total of 180 patients (90 per arm) in two centers. Assessments are conducted pretreatment, after 6 (treatment termination) and 12 months (follow-up). The primary outcome measures are reduction of the depression score in the Hospital Anxiety and Depression Scale and remission of depression as assessed by means of the Structured Clinical Interview for DSM IV Disorders by independent, blinded assessors at treatment termination. Secondary outcomes refer to quality of life.
We investigate the efficacy of short-term psychodynamic psychotherapy in acute care and we aim to identify predictors for acceptance and success of treatment.
Breast cancer; Depression; Short-term psychodynamic psychotherapy; Personality; Helping alliance; Quality of life
Inhibitors targeting the cell cycle-regulated aurora kinase A (AURKA) are currently being developed. Here, we examine the prognostic impact of AURKA in node-negative breast cancer patients without adjuvant systemic therapy (n = 766).
AURKA was analyzed using microarray-based gene-expression data from three independent cohorts of node-negative breast cancer patients. In multivariate Cox analyses, the prognostic impact of age, histological grade, tumor size, estrogen receptor (ER), and HER2 were considered.
Patients with higher AURKA expression had a shorter metastasis-free survival (MFS) in the Mainz (HR 1.93; 95% CI 1.34 – 2.78; P < 0.001), Rotterdam (HR 1.95; 95% CI 1.45– 2.63; P<0.001) and Transbig (HR 1.52; 95% CI 1.14–2.04; P=0.005) cohorts. AURKA was also associated with MFS in the molecular subtype ER+/HER2- carcinomas (HR 2.10; 95% CI 1.70–2.59; P<0.001), but not in ER-/HER2- nor in HER2+ carcinomas. In the multivariate Cox regression adjusted to age, grade and tumor size, AURKA showed independent prognostic significance in the ER+/HER2- subtype (HR 1.73; 95% CI 1.24–2.42; P=0.001). Prognosis of patients in the highest quartile of AURKA expression was particularly poor. In addition, AURKA correlated with the proliferation metagene (R=0.880; P<0.001), showed a positive association with grade (P<0.001), tumor size (P<0.001) and HER2 (P<0.001), and was inversely associated with ER status (P<0.001).
AURKA is associated with worse prognosis in estrogen receptor positive breast carcinomas. Patients with the highest AURKA expression (>75% percentile) have a particularly bad prognosis and may profit from therapy with AURKA inhibitors.
Aurora kinase; Node-negative breast cancer; Breast cancer; Prognosis; Aurora kinase inhibitors
EndoPredict (EP) is a clinically validated multianalyte gene expression test to predict distant metastasis in ER-positive, HER2-negative breast cancer treated with endocrine therapy alone. The test is based on the combined analysis of 12 genes in formalin-fixed, paraffin-embedded (FFPE) tissue by reverse transcription-quantitative real-time PCR (RT-qPCR). Recently, it was shown that EP is feasible for reliable decentralized assessment of gene expression. The aim of this study was the analytical validation of the performance characteristics of the assay and its verification in a molecular-pathological routine laboratory.
Gene expression values to calculate the EP score were assayed by one-step RT-qPCR using RNA from FFPE tumor tissue. Limit of blank, limit of detection, linear range, and PCR efficiency were assessed for each of the 12 PCR assays using serial samples dilutions. Different breast cancer samples were used to evaluate RNA input range, precision and inter-laboratory variability.
PCR assays were linear up to Cq values between 35.1 and 37.2. Amplification efficiencies ranged from 75% to 101%. The RNA input range without considerable change of the EP score was between 0.16 and 18.5 ng/μl. Analysis of precision (variation of day, day time, instrument, operator, reagent lots) resulted in a total noise (standard deviation) of 0.16 EP score units on a scale from 0 to 15. The major part of the total noise (SD 0.14) was caused by the replicate-to-replicate noise of the PCR assays (repeatability) and was not associated with different operating conditions (reproducibility). Performance characteristics established in the manufacturer’s laboratory were verified in a routine molecular pathology laboratory. Comparison of 10 tumor samples analyzed in two different laboratories showed a Pearson coefficient of 0.995 and a mean deviation of 0.15 score units.
The EP test showed reproducible performance characteristics with good precision and negligible laboratory-to-laboratory variation. This study provides further evidence that the EP test is suitable for decentralized testing in specialized molecular pathological laboratories instead of a reference laboratory. This is a unique feature and a technical advance in comparison with existing RNA-based prognostic multigene expression tests.
Breast cancer; Prognostic multigene expression test; Analytical validation; PCR; Pathology
Infiltration of plasma cells is associated with better prognosis in breast, lung and colon cancer. Immunoglobulin κ chain (IGKC) is now available as a single, robust immune marker predicting metastasis-free survival and response to chemotherapy. This will facilitate a deeper understanding of the role of the humoral immune system in cancer development.
breast cancer prognosis; colon cancer; humoral immune system; immunoglobulin kappa C; lung cancer; prediction of chemotherapy response; prognosis
Biomarkers of the immune system are currently not used as prognostic factors in breast cancer. We analyzed the association of the B cell/plasma cell marker immunoglobulin kappa C (IGKC) and survival of untreated node-negative breast cancer patients.
Material and Methods
IGKC expression was evaluated by immunostaining in a cohort of 335 node-negative breast cancer patients with a median follow-up of 152 months. The prognostic significance of IGKC for disease-free survival (DFS) and breast cancer-specific overall survival (OS) was evaluated with Kaplan-Meier survival analysis as well as univariate and multivariate Cox analysis adjusted for age at diagnosis, pT stage, histological grade, estrogen receptor (ER) status, progesterone receptor (PR) status, Ki-67 and human epidermal growth factor receptor 2 (HER-2) status.
160 patients (47.7%) showed strong expression of IGKC. Univariate analysis showed that IGKC was significantly associated with DFS (P = 0.017, hazard ratio [HR] = 0.570, 95% confidence interval [CI] = 0.360–0.903) and OS (P = 0.011, HR = 0.438, 95% CI = 0.233–0.822) in the entire cohort. The significance of IGKC was especially strong in ER negative and in luminal B carcinomas. In multivariate analysis IGKC retained its significance independent of established clinical factors for DFS (P = 0.004, HR = 0.504, 95% CI = 0.315–0.804) as well as for OS (P = 0.002, HR = 0.371, 95% CI = 0.196–0.705).
Expression of IGKC has an independent protective impact on DFS and OS in node-negative breast cancer.
We recently reported that nuclear grading in prostate cancer is subject to a strong confirmation bias induced by the tumor architecture. We now wondered whether a similar bias governs nuclear grading in breast carcinoma. An unannounced test was performed at a pathology conference. Pathologists were asked to grade nuclei in a PowerPoint presentation. Circular high power fields of 27 invasive ductal carcinomas were shown, superimposed over low power background images of either tubule-rich or tubule-poor carcinomas. We found (a) that diagnostic reproducibility of nuclear grades was poor to moderate (weighed kappa values between 0.07 and 0.54, 27 cases, 44 graders), but (b) that nuclear grades were not affected by the tumor architecture. We speculate that the categorized grading in breast cancer, separating tubule formation, nuclear pleomorphism, and mitotic figure counts in a combined three tier score, prevents the bias that architecture exerts on nuclear grades in less well-controlled situations.
Confirmation bias; Cancer grading; Nuclear pleomorphism; Architecture; Cognitive psychology
Afatinib (BIBW 2992) is an ErbB-family blocker that irreversibly inhibits signaling from all relevant ErbB-family dimers. Afatinib has demonstrated preclinical activity in human epidermal growth factor receptor HER2 (ErbB2)-positive and triple-negative xenograft models of breast cancer, and clinical activity in phase I studies. This was a multicenter phase II study enrolling patients with HER2-negative metastatic breast cancer progressing following no more than three lines of chemotherapy. No prior epidermal growth factor receptor-targeted therapy was allowed. Patients received 50-mg afatinib once daily until disease progression. Tumor assessment was performed at every other 28-day treatment course. The primary endpoint was clinical benefit (CB) for ≥4 treatment courses in triple-negative (Cohort A) metastatic breast cancer (TNBC) and objective responses measured by Response Evaluation Criteria in Solid Tumors in patients with HER2-negative, estrogen receptor-positive, and/or progesterone receptor-positive breast cancer (Cohort B). Fifty patients received treatment, including 29 patients in Cohort A and 21 patients in Cohort B. No objective responses were observed in either cohort. Median progression-free survival was 7.4 and 7.7 weeks in Cohorts A and B, respectively. Three patients with TNBC had stable disease for ≥4 treatment courses, one of them for 12 courses (median 26.3 weeks; range 18.9–47.9 weeks). The most frequently observed afatinib-associated adverse events (AEs) were gastrointestinal and skin-related side effects, which were manageable by symptomatic treatment and dose reductions. Afatinib pharmacokinetics were comparable to those observed in previously reported phase I trials. In conclusion, afatinib had limited activity in HER2-negative breast cancer. AEs were generally manageable and mainly affected the skin and the gastrointestinal tract.
Electronic supplementary material
The online version of this article (doi:10.1007/s10549-012-2126-1) contains supplementary material, which is available to authorized users.
Afatinib; Metastatic breast cancer; Triple-negative breast cancer; HER2-negative breast cancer; EGFR TKI
Noninvasive biomarkers are urgently needed for early detection of breast cancer since the risk of recurrence, morbidity and mortality are closely related to disease stage at the time of primary surgery. In the past decade, many proteomics-based approaches were developed that utilize the protein profiling of human body fluids or identification of putative biomarkers to obtain more knowledge on the effects of cancer emergence and progression. Herein, we report on an analysis of proteins in the tear fluid from breast carcinoma patients and healthy women using a de novo proteomic approach and 25 mixed samples from each group. This study included 25 patients with primary invasive breast carcinoma and 25 age-matched healthy controls. We performed a MALDI-TOF-TOF-driven semi-quantitative comparison of tear protein levels in cancer (CA) and control (CTRL) using a de novo approach in pooled samples. Over 150 proteins in the tear fluid of CTRL and CA were identified. Using an in-house-developed algorithm we found more than 20 proteins distinctly upregulated or downregulated in the CTRL and CA groups. We identified several proteins that had modified expression in breast cancer patients. These proteins are involved in host immune system pathways (e.g., C1Q1 or S100A8) and different metabolic cascades (ALDH3A or TPI). Further validation of the results in an independent population combined with individual protein profiling of participants is needed to confirm the specificity of our findings and may lead to a better understanding of the pathological mechanism of breast cancer.
breast cancer; biomarker; diagnosis; proteomics; tear fluids
Children and adolescents who develop schizophrenia tend to have greater symptom severity than adults who develop the illness. Since the brain continues to mature into early adulthood, developmental differences in brain structure and function may provide clues to the underlying neurobiology of schizophrenia. With an emerging body of evidence supporting disrupted connectivity contributing to the underlying pathophysiology of schizophrenia, it was our goal to assess differences in functional connectivity in children and adolescents who develop schizophrenia. Participants included a total of 28 children and adolescents (14 patients with schizophrenia and 14 age- and gender-matched controls). All subjects underwent a functional magnetic resonance imaging scan involving a modified Sternberg Item Recognition Paradigm with 3 working memory (WkM) loads. Patients had poorer performance at all 3 WkM loads without a load by diagnosis interaction. Functional imaging results demonstrated 3 specific brain networks disrupted in children and adolescents with schizophrenia. These networks include 1) the anterior cingulate and the temporal lobes, bilaterally; 2) the cerebellum with subcortical regions; and 3) the occipital lobe and the cerebellum. Patients with early-onset schizophrenia demonstrate abnormal functional connectivity in networks involving limbic, temporal lobe, cerebellum, and early visual processing streams.
cerebellum; early-onset schizophrenia; fMRI; limbic system; prefrontal cortex; temporal lobe
Gene expression profiles provide important information about the biology of breast tumors and can be used to develop prognostic tests. However, the implementation of quantitative RNA-based testing in routine molecular pathology has not been accomplished, so far. The EndoPredict assay has recently been described as a quantitative RT-PCR-based multigene expression test to identify a subgroup of hormone–receptor-positive tumors that have an excellent prognosis with endocrine therapy only. To transfer this test from bench to bedside, it is essential to evaluate the test–performance in a multicenter setting in different molecular pathology laboratories. In this study, we have evaluated the EndoPredict (EP) assay in seven different molecular pathology laboratories in Germany, Austria, and Switzerland. A set of ten formalin-fixed paraffin-embedded tumors was tested in the different labs, and the variance and accuracy of the EndoPredict assays were determined using predefined reference values. Extraction of a sufficient amount of RNA and generation of a valid EP score was possible for all 70 study samples (100%). The EP scores measured by the individual participants showed an excellent correlation with the reference values, respectively, as reflected by Pearson correlation coefficients ranging from 0.987 to 0.999. The Pearson correlation coefficient of all values compared to the reference value was 0.994. All laboratories determined EP scores for all samples differing not more than 1.0 score units from the pre-defined references. All samples were assigned to the correct EP risk group, resulting in a sensitivity and specificity of 100%, a concordance of 100%, and a kappa of 1.0. Taken together, the EndoPredict test could be successfully implemented in all seven participating laboratories and is feasible for reliable decentralized assessment of gene expression in luminal breast cancer.
Breast cancer; Prognosis; mRNA; Quality control
Current prognostic gene signatures for breast cancer mainly reflect proliferation status and have limited value in triple-negative (TNBC) cancers. The identification of prognostic signatures from TNBC cohorts was limited in the past due to small sample sizes.
We assembled all currently publically available TNBC gene expression datasets generated on Affymetrix gene chips. Inter-laboratory variation was minimized by filtering methods for both samples and genes. Supervised analysis was performed to identify prognostic signatures from 394 cases which were subsequently tested on an independent validation cohort (n = 261 cases).
Using two distinct false discovery rate thresholds, 25% and <3.5%, a larger (n = 264 probesets) and a smaller (n = 26 probesets) prognostic gene sets were identified and used as prognostic predictors. Most of these genes were positively associated with poor prognosis and correlated to metagenes for inflammation and angiogenesis. No correlation to other previously published prognostic signatures (recurrence score, genomic grade index, 70-gene signature, wound response signature, 7-gene immune response module, stroma derived prognostic predictor, and a medullary like signature) was observed. In multivariate analyses in the validation cohort the two signatures showed hazard ratios of 4.03 (95% confidence interval [CI] 1.71–9.48; P = 0.001) and 4.08 (95% CI 1.79–9.28; P = 0.001), respectively. The 10-year event-free survival was 70% for the good risk and 20% for the high risk group. The 26-gene signatures had modest predictive value (AUC = 0.588) to predict response to neoadjuvant chemotherapy, however, the combination of a B-cell metagene with the prognostic signatures increased its response predictive value. We identified a 264-gene prognostic signature for TNBC which is unrelated to previously known prognostic signatures.
An important application of high dimensional gene expression measurements is the risk prediction and the interpretation of the variables in the resulting survival models. A major problem in this context is the typically large number of genes compared to the number of observations (individuals). Feature selection procedures can generate predictive models with high prediction accuracy and at the same time low model complexity. However, interpretability of the resulting models is still limited due to little knowledge on many of the remaining selected genes. Thus, we summarize genes as gene groups defined by the hierarchically structured Gene Ontology (GO) and include these gene groups as covariates in the hazard regression models. Since expression profiles within GO groups are often heterogeneous, we present a new method to obtain subgroups with coherent patterns. We apply preclustering to genes within GO groups according to the correlation of their gene expression measurements.
We compare Cox models for modeling disease free survival times of breast cancer patients. Besides classical clinical covariates we consider genes, GO groups and preclustered GO groups as additional genomic covariates. Survival models with preclustered gene groups as covariates have similar prediction accuracy as models built only with single genes or GO groups.
The preclustering information enables a more detailed analysis of the biological meaning of covariates selected in the final models. Compared to models built only with single genes there is additional functional information contained in the GO annotation, and compared to models using GO groups as covariates the preclustering yields coherent representative gene expression profiles.
The prognosis of patients with recurrent, platinum-resistant epithelial ovarian cancer (EOC) is poor. There is no standard treatment available. Emerging evidence suggests a major role for antiangiogenic treatment modalities in EOC, in particular in combination with the metronomic application of low dose chemotherapy. The novel, investigational oral antiangiogenic agent pazopanib targeting vascular endothelial growth factor receptor (VEGFR), platelet-derived growth factor receptor (PDGFR) and c-kit is currently being studied in different tumour types and is already used as first line therapy in recurrent renal cell carcinoma. A combined therapy consisting of pazopanib and metronomic oral cyclophosphamide may offer a well-tolerable treatment option to patients with recurrent, pretreated EOC.
This study is designed as a multicenter phase I/II trial evaluating the optimal dose for pazopanib (phase I) as well as activity and tolerability of a combination regimen consisting of pazopanib and metronomic cyclophosphamide in the palliative treatment of patients with recurrent, platinum-resistant, pre-treated ovarian cancer (phase II). The patient population includes patients with histologically or cytologically confirmed diagnosis of EOC, cancer of the fallopian tube or peritoneal cancer which is platinumresistant or -refractory. Patients must have measurable disease according to RECIST criteria and must have failed available standard chemotherapy. Primary objectives are determination of the optimal doses for pazopanib (phase I) and the overall response rate according to RECIST criteria (phase II). Secondary objectives are time to progression, overall survival, safety and tolerability. The treatment duration is until disease progression or intolerability of study drug regimen (with a maximum of 13 cycles up to 52 weeks per subject).
The current phase I/II trial shall clarify the potential of the multitargeting antiangiogenic tyrosinkinaseinhibitor GW 786034 (pazopanib) in combination with oral cyclophosphamide as salvage treatment in patients with recurrent, pretreated ovarian cancer.
Current prognostic gene expression profiles for breast cancer mainly reflect proliferation status and are most useful in ER-positive cancers. Triple negative breast cancers (TNBC) are clinically heterogeneous and prognostic markers and biology-based therapies are needed to better treat this disease.
We assembled Affymetrix gene expression data for 579 TNBC and performed unsupervised analysis to define metagenes that distinguish molecular subsets within TNBC. We used n = 394 cases for discovery and n = 185 cases for validation. Sixteen metagenes emerged that identified basal-like, apocrine and claudin-low molecular subtypes, or reflected various non-neoplastic cell populations, including immune cells, blood, adipocytes, stroma, angiogenesis and inflammation within the cancer. The expressions of these metagenes were correlated with survival and multivariate analysis was performed, including routine clinical and pathological variables.
Seventy-three percent of TNBC displayed basal-like molecular subtype that correlated with high histological grade and younger age. Survival of basal-like TNBC was not different from non basal-like TNBC. High expression of immune cell metagenes was associated with good and high expression of inflammation and angiogenesis-related metagenes were associated with poor prognosis. A ratio of high B-cell and low IL-8 metagenes identified 32% of TNBC with good prognosis (hazard ratio (HR) 0.37, 95% CI 0.22 to 0.61; P < 0.001) and was the only significant predictor in multivariate analysis including routine clinicopathological variables.
We describe a ratio of high B-cell presence and low IL-8 activity as a powerful new prognostic marker for TNBC. Inhibition of the IL-8 pathway also represents an attractive novel therapeutic target for this disease.
Today, more than 70% of patients with primary node-negative breast cancer are cured by local therapy alone. Many patients receive overtreatment by adjuvant chemotherapy due to inadequate risk assessment. So far, few clinical trials have prospectively evaluated tumor biology based prognostic factors. Risk assessment by a biological algorithm including invasion factors urokinase-type plasminogen activator (uPA) and its inhibitor plasminogen activator inhibitor type 1 (PAI-1) will assess up to 35-55% of node-negative patients as low-risk and thus avoid chemotherapy. In contrast, a clinical-pathological algorithm will only classify 20-40% of patients as low-risk. High-risk node-negative patients should receive chemotherapy. Anthracycline-based regimens are accepted as a standard, the additional benefit of taxanes remains an open question.
The international NNBC3 ("Node Negative Breast Cancer 3-Europe") trial compares biological risk assessment (UP) using invasion factors uPA/PAI-1 with a clinical-pathological algorithm (CP). In this trial, the type of risk assessment (CP or UP) was chosen upfront by each center for its patients. Fresh frozen tissue was obtained to determine uPA/PAI-1 using an enzyme-linked immunosorbent assay (ELISA). Patients assessed as high-risk were stratified by human epidermal growth factor receptor 2 (HER2) status and then randomised to receive anthracycline-containing chemotherapy 5-Fluorouracil (F)/Epirubicin (E)/Cyclophosphymide (C) or an anthracycline-taxane sequence (FE100C*6 versus FE100C*3 followed by Docetaxel100*3).
In this trial, 4,149 node-negative patients with operable breast cancer from 153 centers in Germany and France were included since 2002. Measurement of uPA/PAI-1 by ELISA was performed with standardised central quality assurance for 2,497 patients (60%) from 56 "UP"-centers. The NNBC 3-Europe trial showed that inclusion of patients into a clinical phase III trial is feasible based on biological testing of fresh frozen tumor material. In addition, 2,661 patients were classified as high-risk and thus received chemotherapy. As adjuvant chemotherapy, 1,334 high-risk patients received FE100C-Docetaxel100, and 1,327 received French FE100C. No unexpected toxicities were observed. Chemotherapy efficacy and comparison of UP with CP will be evaluated after longer follow-up.
clinical Trials.gov NCT01222052.
Gyrification is the process by which the brain undergoes changes in surface morphology to create sulcal and gyral regions. The period of greatest development of brain gyrification is during the third trimester of pregnancy, a period of time in which the brain undergoes considerable growth. Little is known about changes in gyrification during childhood and adolescence, although considering the changes in gray matter volume and thickness during this time period, it is conceivable that alterations in the brain surface morphology could also occur during this period of development. The formation of gyri and sulci in the brain allows for compact wiring that promotes and enhances efficient neural processing. If cerebral function and form are linked through the organization of neural connectivity, then alterations in neural connectivity, i.e., synaptic pruning, may also alter the gyral and sulcal patterns of the brain. This paper reviews developmental theories of gyrification, computational techniques for measuring gyrification, and the potential interaction between gyrification and neuronal connectivity. We also present recent findings involving alterations in gyrification during childhood and adolescence.
Gyrification; Adolescence; Development; Connectivity; Cortical Morphology
There is considerable evidence implicating white matter abnormalities in the pathophysiology of schizophrenia. Many of the recent studies examining white matter have utilized diffusion tensor imaging (DTI) using either region of interest (ROI) or voxel based approaches. Both voxel-based and ROI approaches are based on the assumption that the abnormalities in white matter overlap spatially. However, this is an assumption that has not been tested and it is possible that aberrations in white matter occur in non-overlapping regions. In order to test for the presence of non-overlapping regions of aberrant white matter, we developed a novel image processing technique that evaluates for white matter ‘potholes,’ referring to within-subject clusters of white matter voxels that show a significant reduction in fractional anisotropy. We applied this algorithm to a group of children and adolescents with schizophrenia compared to controls and found an increased number of ‘potholes’ in the patient group. These results suggest that voxel-based and ROI approaches may be missing some white matter differences that do not overlap spatially. This algorithm may be also be well suited to detect white matter abnormalities in disorders such as substance abuse, head trauma, or specifc neurological conditions affecting white matter.
DTI; Imaging Methods; Early-Onset Schizophrenia; Potholes
Elucidating the activation pattern of molecular pathways across a given tumour type is a key challenge necessary for understanding the heterogeneity in clinical response and for developing novel more effective therapies. Gene expression signatures of molecular pathway activation derived from perturbation experiments in model systems as well as structural models of molecular interactions ("model signatures") constitute an important resource for estimating corresponding activation levels in tumours. However, relatively few strategies for estimating pathway activity from such model signatures exist and only few studies have used activation patterns of pathways to refine molecular classifications of cancer.
Here we propose a novel network-based method for estimating pathway activation in tumours from model signatures. We find that although the pathway networks inferred from cancer expression data are highly consistent with the prior information contained in the model signatures, that they also exhibit a highly modular structure and that estimation of pathway activity is dependent on this modular structure. We apply our methodology to a panel of 438 estrogen receptor negative (ER-) and 785 estrogen receptor positive (ER+) breast cancers to infer activation patterns of important cancer related molecular pathways.
We show that in ER negative basal and HER2+ breast cancer, gene expression modules reflecting T-cell helper-1 (Th1) and T-cell helper-2 (Th2) mediated immune responses play antagonistic roles as major risk factors for distant metastasis. Using Boolean interaction Cox-regression models to identify non-linear pathway combinations associated with clinical outcome, we show that simultaneous high activation of Th1 and low activation of a TGF-beta pathway module defines a subtype of particularly good prognosis and that this classification provides a better prognostic model than those based on the individual pathways. In ER+ breast cancer, we find that simultaneous high MYC and RAS activity confers significantly worse prognosis than either high MYC or high RAS activity alone. We further validate these novel prognostic classifications in independent sets of 173 ER- and 567 ER+ breast cancers.
We have proposed a novel method for pathway activity estimation in tumours and have shown that pathway modules antagonize or synergize to delineate novel prognostic subtypes. Specifically, our results suggest that simultaneous modulation of T-helper differentiation and TGF-beta pathways may improve clinical outcome of hormone insensitive breast cancers over treatments that target only one of these pathways.
The integration of the non-cross-resistant chemotherapeutic agents capecitabine and vinorelbine into an intensified dose-dense sequential anthracycline- and taxane-containing regimen in high-risk early breast cancer (EBC) could improve efficacy, but this combination was not examined in this context so far.
Patients with stage II/IIIA EBC (four or more positive lymph nodes) received post-operative intensified dose-dense sequential epirubicin (150 mg/m² every 2 weeks) and paclitaxel (225 mg/m² every 2 weeks) with filgrastim and darbepoetin alfa, followed by capecitabine alone (dose levels 1 and 3) or with vinorelbine (dose levels 2 and 4). Capecitabine was given on days 1-14 every 21 days at 1000 or 1250 mg/m2 twice daily (dose levels 1/2 and 3/4, respectively). Vinorelbine 25 mg/m2 was given on days 1 and 8 of each 21-day course (dose levels 2 and 4).
Fifty-one patients were treated. There was one dose-limiting toxicity (DLT) at dose level 1. At dose level 2 (capecitabine and vinorelbine), five of 10 patients experienced DLTs. Therefore evaluation of vinorelbine was abandoned and dose level 3 (capecitabine monotherapy) was expanded. Hand-foot syndrome and diarrhoea were dose limiting with capecitabine 1250 mg/m2 twice daily. At 35.2 months' median follow-up, the estimated 3-year relapse-free and overall survival rates were 82% and 91%, respectively.
Administration of capecitabine monotherapy after sequential dose-dense epirubicin and paclitaxel is feasible in node-positive EBC, while the combination of capecitabine and vinorelbine as used here caused more DLTs.
Current Controlled Trials ISRCTN38983527.
The purpose of this work was to study the prognostic influence in breast cancer of thioredoxin reductase 1 (TXNRD1) and thioredoxin interacting protein (TXNIP), key players in oxidative stress control that are currently evaluated as possible therapeutic targets.
Analysis of the association of TXNRD1 and TXNIP RNA expression with the metastasis-free interval (MFI) was performed in 788 patients with node-negative breast cancer, consisting of three individual cohorts (Mainz, Rotterdam and Transbig). Correlation with metagenes and conventional clinical parameters (age, pT stage, grading, hormone and ERBB2 status) was explored. MCF-7 cells with a doxycycline-inducible expression of an oncogenic ERBB2 were used to investigate the influence of ERBB2 on TXNRD1 and TXNIP transcription.
TXNRD1 was associated with worse MFI in the combined cohort (hazard ratio = 1.955; P < 0.001) as well as in all three individual cohorts. In contrast, TXNIP was associated with better prognosis (hazard ratio = 0.642; P < 0.001) and similar results were obtained in all three subcohorts. Interestingly, patients with ERBB2-status-positive tumors expressed higher levels of TXNRD1. Induction of ERBB2 in MCF-7 cells caused not only an immediate increase in TXNRD1 but also a strong decrease in TXNIP. A subsequent upregulation of TXNIP as cells undergo senescence was accompanied by a strong increase in levels of reactive oxygen species.
TXNRD1 and TXNIP are associated with prognosis in breast cancer, and ERBB2 seems to be one of the factors shifting balances of both factors of the redox control system in a prognostic unfavorable manner.
A major goal of the analysis of high-dimensional RNA expression data from tumor tissue is to identify prognostic signatures for discriminating patient subgroups. For this purpose genome-wide identification of bimodally expressed genes from gene array data is relevant because distinguishability of high and low expression groups is easier compared to genes with unimodal expression distributions.
Recently, several methods for the identification of genes with bimodal distributions have been introduced. A straightforward approach is to cluster the expression values and score the distance between the two distributions. Other scores directly measure properties of the distribution. The kurtosis, e.g., measures divergence from a normal distribution. An alternative is the outlier-sum statistic that identifies genes with extremely high or low expression values in a subset of the samples.
We compare and discuss scores for bimodality for expression data. For the genome-wide identification of bimodal genes we apply all scores to expression data from 194 patients with node-negative breast cancer. Further, we present the first comprehensive genome-wide evaluation of the prognostic relevance of bimodal genes. We first rank genes according to bimodality scores and define two patient subgroups based on expression values. Then we assess the prognostic significance of the top ranking bimodal genes by comparing the survival functions of the two patient subgroups. We also evaluate the global association between the bimodal shape of expression distributions and survival times with an enrichment type analysis.
Various cluster-based methods lead to a significant overrepresentation of prognostic genes. A striking result is obtained with the outlier-sum statistic (p < 10-12). Many genes with heavy tails generate subgroups of patients with different prognosis.
Genes with high bimodality scores are promising candidates for defining prognostic patient subgroups from expression data. We discuss advantages and disadvantages of the different scores for prognostic purposes. The outlier-sum statistic may be particularly valuable for the identification of genes to be included in prognostic signatures. Among the genes identified as bimodal in the breast cancer data set several have not yet previously been recognized to be prognostic and bimodally expressed in breast cancer.
Pegylated liposomal doxorubicin (PLD) is active in metastatic breast cancer. This observational study evaluated the efficacy and safety of PLD in patients treated during routine clinical practice.
Eligible patients had metastatic breast cancer and were treated with PLD according to the dose and schedule determined by their physician as part of routine practice. The primary objectives were to analyze the efficacy and toxicity of PLD therapy.
125 patients were assessable. Median age was 62 years, 78% had performance status 0-1, and 60% had estrogen-receptor-positive disease. PLD treatment was second- or third-line in 69% of patients. Prior anthracyclines (adjuvant or metastatic) had been used in 56% of patients. The majority of patients (79%) received PLD every 4 weeks at a median dose of 40 mg/m2. Overall response rate was 43% in all patients and 34% in those previously treated with anthracyclines. The most common grade 3/4 adverse events were skin toxicity/hand-foot syndrome (6%), and leukopenia (3%).
This observational study supports the activity and tolerability of PLD in metastatic breast cancer as demonstrated in PLD clinical trials.