Benefits of biomarker selection and clinico-pathological covariate inclusion in breast cancer prognostic models

Introduction: Multi-marker molecular assays have impacted management of early stage breast cancer, facilitating adjuvant chemotherapy decisions. We generated prognostic models that incorporate protein-based molecular markers and clinico-pathological variables to improve survival prediction. Methods: We used a quantitative immunofluorescence method to study protein expression of 14 markers included in the Oncotype DX™ assay on a 638 breast cancer patient cohort with 15-year follow-up. We performed cross-validation analyses to assess performance of multivariate Cox models consisting of these markers and standard clinico-pathological covariates, using an average time-dependent Area Under the Receiver Operating Characteristic curves and compared it to nested Cox models obtained by robust backward selection procedures. Results: A prognostic index derived from of a multivariate Cox regression model incorporating molecular and clinico-pathological covariates (nodal status, tumor size, nuclear grade, and age) is superior to models based on molecular studies alone or clinico-pathological covariates alone. Performance of this composite model can be further improved using feature selection techniques to prune variables. When stratifying patients by Nottingham Prognostic Index (NPI), the most prognostic markers in high and low NPI groups differed. Similarly, for the node-negative, hormone receptor-positive sub-population, we derived a compact model with three clinico-pathological variables and two protein markers that was superior to the full model. Conclusions: Prognostic models that include both molecular and clinico-pathological covariates can be more accurate than models based on either set of features alone. Furthermore, feature selection can decrease the number of molecular variables needed to predict outcome, potentially resulting in less expensive assays.This work was supported by a grant from the Susan G Komen Foundation (to YK)

Exploring efficient seamless handover in VANET systems using network dwell time

Vehicular ad hoc networks are a long-term solution contributing significantly towards intelligent transport systems (ITS) in providing access to critical life-safety applications and services. Although vehicular ad hoc networks are attracting greater commercial interest, current research has not adequately captured the real-world constraints in vehicular ad hoc network handover techniques. Therefore, in order to have the best practice for vehicular ad hoc network services, it is necessary to have seamless connectivity for optimal coverage and ideal channel utilisation. Due to the high velocity of vehicles and smaller coverage distances, there are serious challenges in providing seamless handover from one roadside unit (RSU) to another. Though other research efforts have looked at many issues in vehicular ad hoc networks (VANETs), very few research work have looked at handover issues. Most literature assume that handover does not take a significant time and does not affect the overall VANET operation. In our previous work, we started to investigate these issues. This journal provides a more comprehensive analysis involving the beacon frequency, the size of beacon and the velocity of the vehicle. We used some of the concepts of Y-Comm architecture such as network dwell time (NDT), time before handover (TBH) and exit time (ET) to provide a framework to investigate handover issues. Further simulation studies were used to investigate the relation between beaconing, velocity and the network dwell time. Our results show that there is a need to understand the cumulative effect of beaconing in addition to the probability of successful reception as well as how these probability distributions are affected by the velocity of the vehicle. This provides more insight into how to support life critical applications using proactive handover techniques

Granular Assembly of α-Synuclein Leading to the Accelerated Amyloid Fibril Formation with Shear Stress

α-Synuclein participates in the Lewy body formation of Parkinson's disease. Elucidation of the underlying molecular mechanism of the amyloid fibril formation is crucial not only to develop a controlling strategy toward the disease, but also to apply the protein fibrils for future biotechnology. Discernable homogeneous granules of α-synuclein composed of approximately 11 monomers in average were isolated in the middle of a lag phase during the in vitro fibrillation process. They were demonstrated to experience almost instantaneous fibrillation during a single 12-min centrifugal membrane-filtration at 14,000×g. The granular assembly leading to the drastically accelerated fibril formation was demonstrated to be a result of the physical influence of shear force imposed on the preformed granular structures by either centrifugal filtration or rheometer. Structural rearrangement of the preformed oligomomeric structures is attributable for the suprastructure formation in which the granules act as a growing unit for the fibril formation. To parallel the prevailing notion of nucleation-dependent amyloidosis, we propose a double-concerted fibrillation model as one of the mechanisms to explain the in vitro fibrillation of α-synuclein, in which two consecutive concerted associations of monomers and subsequent oligomeric granular species are responsible for the eventual amyloid fibril formation

Enhanced NFκB and AP-1 transcriptional activity associated with antiestrogen resistant breast cancer

BACKGROUND: Signaling pathways that converge on two different transcription factor complexes, NFκB and AP-1, have been identified in estrogen receptor (ER)-positive breast cancers resistant to the antiestrogen, tamoxifen. METHODS: Two cell line models of tamoxifen-resistant ER-positive breast cancer, MCF7/HER2 and BT474, showing increased AP-1 and NFκB DNA-binding and transcriptional activities, were studied to compare tamoxifen effects on NFκB and AP-1 regulated reporter genes relative to tamoxifen-sensitive MCF7 cells. The model cell lines were treated with the IKK inhibitor parthenolide (PA) or the proteasome inhibitor bortezomib (PS341), alone and in combination with tamoxifen. Expression microarray data available from 54 UCSF node-negative ER-positive breast cancer cases with known clinical outcome were used to search for potential genes signifying upregulated NFκB and AP-1 transcriptional activity in association with tamoxifen resistance. The association of these genes with patient outcome was further evaluated using node-negative ER-positive breast cancer cases identified from three other published data sets (Rotterdam, n = 209; Amsterdam, n = 68; Basel, n = 108), each having different patient age and adjuvant tamoxifen treatment characteristics. RESULTS: Doses of parthenolide and bortezomib capable of sensitizing the two endocrine resistant breast cancer models to tamoxifen were capable of suppressing NFκB and AP-1 regulated gene expression in combination with tamoxifen and also increased ER recruitment of the transcriptional co-repressor, NCoR. Transcript profiles from the UCSF breast cancer cases revealed three NFκB and AP-1 upregulated genes – cyclin D1, uPA and VEGF – capable of dichotomizing node-negative ER-positive cases into early and late relapsing subsets despite adjuvant tamoxfien therapy and most prognostic for younger age cases. Across the four independent sets of node-negative ER-positive breast cancer cases (UCSF, Rotterdam, Amsterdam, Basel), high expression of all three NFκB and AP-1 upregulated genes was associated with earliest metastatic relapse. CONCLUSION: Altogether, these findings implicate increased NFκB and AP-1 transcriptional responses with tamoxifen resistant breast cancer and early metastatic relapse, especially in younger patients. These findings also suggest that agents capable of preventing NFκB and AP-1 gene activation may prove useful in restoring the endocrine responsiveness of such high-risk ER-positive breast cancers

Communicating simply, but not too simply: Reporting of participants and speech and language interventions for aphasia after stroke

Purpose: Speech and language pathology (SLP) for aphasia is a complex intervention delivered to a heterogeneous population within diverse settings. Simplistic descriptions of participants and interventions in research hinder replication, interpretation of results, guideline and research developments through secondary data analyses. This study aimed to describe the availability of participant and intervention descriptors in existing aphasia research datasets. Method: We systematically identified aphasia research datasets containing ≥10 participants with information on time since stroke and language ability. We extracted participant and SLP intervention descriptions and considered the availability of data compared to historical and current reporting standards. We developed an extension to the Template for Intervention Description and Replication checklist to support meaningful classification and synthesis of the SLP interventions to support secondary data analysis. Result: Of 11, 314 identified records we screened 1131 full texts and received 75 dataset contributions. We extracted data from 99 additional public domain datasets. Participant age (97.1%) and sex (90.8%) were commonly available. Prior stroke (25.8%), living context (12.1%) and socio-economic status (2.3%) were rarely available. Therapy impairment target, frequency and duration were most commonly available but predominately described at group level. Home practice (46.3%) and tailoring (functional relevance 46.3%) were inconsistently available. Conclusion : Gaps in the availability of participant and intervention details were significant, hampering clinical implementation of evidence into practice and development of our field of research. Improvements in the quality and consistency of participant and intervention data reported in aphasia research are required to maximise clinical implementation, replication in research and the generation of insights from secondary data analysis

Utilising a systematic review-based approach to create a database of individual participant data for meta- and network meta-analyses: the RELEASE database of aphasia after stroke

Background: Collation of aphasia research data across settings, countries and study designs using big data principles will support analyses across different language modalities, levels of impairment, and therapy interventions in this heterogeneous population. Big data approaches in aphasia research may support vital analyses, which are unachievable within individual trial datasets. However, we lack insight into the requirements for a systematically created database, the feasibility and challenges and potential utility of the type of data collated. Aim: To report the development, preparation and establishment of an internationally agreed aphasia after stroke research database of individual participant data (IPD) to facilitate planned aphasia research analyses. Methods: Data were collated by systematically identifying existing, eligible studies in any language (≥10 IPD, data on time since stroke, and language performance) and included sourcing from relevant aphasia research networks. We invited electronic contributions and also extracted IPD from the public domain. Data were assessed for completeness, validity of value-ranges within variables, and described according to pre-defined categories of demographic data, therapy descriptions, and language domain measurements. We cleaned, clarified, imputed and standardised relevant data in collaboration with the original study investigators. We presented participant, language, stroke, and therapy data characteristics of the final database using summary statistics. Results: From 5256 screened records, 698 datasets were potentially eligible for inclusion; 174 datasets (5928 IPD) from 28 countries were included, 47/174 RCT datasets (1778 IPD) and 91/174 (2834 IPD) included a speech and language therapy (SLT) intervention. Participants’ median age was 63 years (interquartile range [53, 72]), 3407 (61.4%) were male and median recruitment time was 321 days (IQR 30, 1156) after stroke. IPD were available for aphasia severity or ability overall (n = 2699; 80 datasets), naming (n = 2886; 75 datasets), auditory comprehension (n = 2750; 71 datasets), functional communication (n = 1591; 29 datasets), reading (n = 770; 12 datasets) and writing (n = 724; 13 datasets). Information on SLT interventions were described by theoretical approach, therapy target, mode of delivery, setting and provider. Therapy regimen was described according to intensity (1882 IPD; 60 datasets), frequency (2057 IPD; 66 datasets), duration (1960 IPD; 64 datasets) and dosage (1978 IPD; 62 datasets). Discussion: Our international IPD archive demonstrates the application of big data principles in the context of aphasia research; our rigorous methodology for data acquisition and cleaning can serve as a template for the establishment of similar databases in other research areas

Predictors of Poststroke Aphasia Recovery A Systematic Review-Informed Individual Participant Data Meta-Analysis

Background and Purpose: The factors associated with recovery of language domains after stroke remain uncertain. We described recovery of overall-language-ability, auditory comprehension, naming, and functional-communication across participants’ age, sex, and aphasia chronicity in a large, multilingual, international aphasia dataset. / Methods: Individual participant data meta-analysis of systematically sourced aphasia datasets described overall-language ability using the Western Aphasia Battery Aphasia-Quotient; auditory comprehension by Aachen Aphasia Test (AAT) Token Test; naming by Boston Naming Test and functional-communication by AAT Spontaneous-Speech Communication subscale. Multivariable analyses regressed absolute score-changes from baseline across language domains onto covariates identified a priori in randomized controlled trials and all study types. Change-from-baseline scores were presented as estimates of means and 95% CIs. Heterogeneity was described using relative variance. Risk of bias was considered at dataset and meta-analysis level. / Results: Assessments at baseline (median=43.6 weeks poststroke; interquartile range [4–165.1]) and first-follow-up (median=10 weeks from baseline; interquartile range [3–26]) were available for n=943 on overall-language ability, n=1056 on auditory comprehension, n=791 on naming and n=974 on functional-communication. Younger age (<55 years, +15.4 Western Aphasia Battery Aphasia-Quotient points [CI, 10.0–20.9], +6.1 correct on AAT Token Test [CI, 3.2–8.9]; +9.3 Boston Naming Test points [CI, 4.7–13.9]; +0.8 AAT Spontaneous-Speech Communication subscale points [CI, 0.5–1.0]) and enrollment <1 month post-onset (+19.1 Western Aphasia Battery Aphasia-Quotient points [CI, 13.9–24.4]; +5.3 correct on AAT Token Test [CI, 1.7–8.8]; +11.1 Boston Naming Test points [CI, 5.7–16.5]; and +1.1 AAT Spontaneous-Speech Communication subscale point [CI, 0.7–1.4]) conferred the greatest absolute change-from-baseline across each language domain. Improvements in language scores from baseline diminished with increasing age and aphasia chronicity. Data exhibited no significant statistical heterogeneity. Risk-of-bias was low to moderate-low. / Conclusions: Earlier intervention for poststroke aphasia was crucial to maximize language recovery across a range of language domains, although recovery continued to be observed to a lesser extent beyond 6 months poststroke

Complex speech-language therapy interventions for stroke-related aphasia: The RELEASE study incorporating a systematic review and individual participant data network meta-analysis

Background: People with language problems following stroke (aphasia) benefit from speech and language therapy. Optimising speech and language therapy for aphasia recovery is a research priority. Objectives: The objectives were to explore patterns and predictors of language and communication recovery, optimum speech and language therapy intervention provision, and whether or not effectiveness varies by participant subgroup or language domain. Design: This research comprised a systematic review, a meta-analysis and a network meta-analysis of individual participant data. Setting: Participant data were collected in research and clinical settings. Interventions: The intervention under investigation was speech and language therapy for aphasia after stroke. Main outcome measures: The main outcome measures were absolute changes in language scores from baseline on overall language ability, auditory comprehension, spoken language, reading comprehension, writing and functional communication. Data sources and participants: Electronic databases were systematically searched, including MEDLINE, EMBASE, Cumulative Index to Nursing and Allied Health Literature, Linguistic and Language Behavior Abstracts and SpeechBITE (searched from inception to 2015). The results were screened for eligibility, and published and unpublished data sets (randomised controlled trials, non-randomised controlled trials, cohort studies, case series, registries) with at least 10 individual participant data reporting aphasia duration and severity were identified. Existing collaborators and primary researchers named in identified records were invited to contribute electronic data sets. Individual participant data in the public domain were extracted. Review methods: Data on demographics, speech and language therapy interventions, outcomes and quality criteria were independently extracted by two reviewers, or available as individual participant data data sets. Meta-analysis and network meta-analysis were used to generate hypotheses. Results: We retrieved 5928 individual participant data from 174 data sets across 28 countries, comprising 75 electronic (3940 individual participant data), 47 randomised controlled trial (1778 individual participant data) and 91 speech and language therapy intervention (2746 individual participant data) data sets. The median participant age was 63 years (interquartile range 53-72 years). We identified 53 unavailable, but potentially eligible, randomised controlled trials (46 of these appeared to include speech and language therapy). Relevant individual participant data were filtered into each analysis. Statistically significant predictors of recovery included age (functional communication, individual participant data: 532, n = 14 randomised controlled trials) and sex (overall language ability, individual participant data: 482, n = 11 randomised controlled trials; functional communication, individual participant data: 532, n = 14 randomised controlled trials). Older age and being a longer time since aphasia onset predicted poorer recovery. A negative relationship between baseline severity score and change from baseline (p < 0.0001) may reflect the reduced improvement possible from high baseline scores. The frequency, duration, intensity and dosage of speech and language therapy were variously associated with auditory comprehension, naming and functional communication recovery. There were insufficient data to examine spontaneous recovery. The greatest overall gains in language ability [14.95 points (95% confidence interval 8.7 to 21.2 points) on the Western Aphasia Battery-Aphasia Quotient] and functional communication [0.78 points (95% confidence interval 0.48 to 1.1 points) on the Aachen Aphasia Test-Spontaneous Communication] were associated with receiving speech and language therapy 4 to 5 days weekly; for auditory comprehension [5.86 points (95% confidence interval 1.6 to 10.0 points) on the Aachen Aphasia Test-Token Test], the greatest gains were associated with receiving speech and language therapy 3 to 4 days weekly. The greatest overall gains in language ability [15.9 points (95% confidence interval 8.0 to 23.6 points) on the Western Aphasia Battery-Aphasia Quotient] and functional communication [0.77 points (95% confidence interval 0.36 to 1.2 points) on the Aachen Aphasia Test-Spontaneous Communication] were associated with speech and language therapy participation from 2 to 4 (and more than 9) hours weekly, whereas the highest auditory comprehension gains [7.3 points (95% confidence interval 4.1 to 10.5 points) on the Aachen Aphasia Test-Token Test] were associated with speech and language therapy participation in excess of 9 hours weekly (with similar gains notes for 4 hours weekly). While clinically similar gains were made alongside different speech and language therapy intensities, the greatest overall gains in language ability [18.37 points (95% confidence interval 10.58 to 26.16 points) on the Western Aphasia Battery-Aphasia Quotient] and auditory comprehension [5.23 points (95% confidence interval 1.51 to 8.95 points) on the Aachen Aphasia Test-Token Test] were associated with 20-50 hours of speech and language therapy. Network meta-analyses on naming and the duration of speech and language therapy interventions across language outcomes were unstable. Relative variance was acceptable (< 30%). Subgroups may benefit from specific interventions. Limitations: Data sets were graded as being at a low risk of bias but were predominantly based on highly selected research participants, assessments and interventions, thereby limiting generalisability. Conclusions: Frequency, intensity and dosage were associated with language gains from baseline, but varied by domain and subgroup

Identification of Functional Networks of Estrogen- and c-Myc-Responsive Genes and Their Relationship to Response to Tamoxifen Therapy in Breast Cancer

BACKGROUND: Estrogen is a pivotal regulator of cell proliferation in the normal breast and breast cancer. Endocrine therapies targeting the estrogen receptor are effective in breast cancer, but their success is limited by intrinsic and acquired resistance. METHODOLOGY/PRINCIPAL FINDINGS: With the goal of gaining mechanistic insights into estrogen action and endocrine resistance, we classified estrogen-regulated genes by function, and determined the relationship between functionally-related genesets and the response to tamoxifen in breast cancer patients. Estrogen-responsive genes were identified by transcript profiling of MCF-7 breast cancer cells. Pathway analysis based on functional annotation of these estrogen-regulated genes identified gene signatures with known or predicted roles in cell cycle control, cell growth (i.e. ribosome biogenesis and protein synthesis), cell death/survival signaling and transcriptional regulation. Since inducible expression of c-Myc in antiestrogen-arrested cells can recapitulate many of the effects of estrogen on molecular endpoints related to cell cycle progression, the estrogen-regulated genes that were also targets of c-Myc were identified using cells inducibly expressing c-Myc. Selected genes classified as estrogen and c-Myc targets displayed similar levels of regulation by estrogen and c-Myc and were not estrogen-regulated in the presence of siMyc. Genes regulated by c-Myc accounted for 50% of all acutely estrogen-regulated genes but comprised 85% (110/129 genes) in the cell growth signature. siRNA-mediated inhibition of c-Myc induction impaired estrogen regulation of ribosome biogenesis and protein synthesis, consistent with the prediction that estrogen regulates cell growth principally via c-Myc. The 'cell cycle', 'cell growth' and 'cell death' gene signatures each identified patients with an attenuated response in a cohort of 246 tamoxifen-treated patients. In multivariate analysis the cell death signature was predictive independent of the cell cycle and cell growth signatures. CONCLUSIONS/SIGNIFICANCE: These functionally-based gene signatures can stratify patients treated with tamoxifen into groups with differing outcome, and potentially identify distinct mechanisms of tamoxifen resistance

Micro-RNAs as diagnostic or prognostic markers in human epithelial malignancies

Micro-RNAs (miRs) are important regulators of mRNA and protein expression; the ability of miR expression profilings to distinguish different cancer types and classify their sub-types has been well-described. They also represent a novel biological entity with potential value as tumour biomarkers, which can improve diagnosis, prognosis, and monitoring of treatment response for human cancers. This endeavour has been greatly facilitated by the stability of miRs in formalin-fixed paraffin-embedded (FFPE) tissues, and their detection in circulation. This review will summarize some of the key dysregulated miRs described to date in human epithelial malignancies, and their potential value as molecular bio-markers in FFPE tissues and blood samples. There remain many challenges in this domain, however, with the evolution of different platforms, the complexities of normalizing miR profiling data, and the importance of evaluating sufficiently-powered training and validation cohorts. Nonetheless, well-conducted miR profiling studies should contribute important insights into the molecular aberrations driving human cancer development and progression