Periodontal dysbiosis associates with reduced CSF Aβ42 in cognitively normal elderly

Introduction: Periodontal disease is a chronic, inflammatory bacterial dysbiosis that is associated with both Alzheimer's disease (AD) and Down syndrome. / Methods: A total of 48 elderly cognitively normal subjects were evaluated for differences in subgingival periodontal bacteria (assayed by 16S rRNA sequencing) between cerebrospinal fluid (CSF) biomarker groups of amyloid and neurofibrillary pathology. A dysbiotic index (DI) was defined at the genus level as the abundance ratio of known periodontal bacteria to healthy bacteria. Analysis of variance/analysis of covariance (ANOVA/ANCOVA), linear discriminant effect‐size analyses (LEfSe) were used to determine the bacterial genera and species differences between the CSF biomarker groups. / Results: At genera and species levels, higher subgingival periodontal dysbiosis was associated with reduced CSF amyloid beta (Aβ)42 (P = 0.02 and 0.01) but not with P‐tau. / Discussion: We show a selective relationship between periodontal disease bacterial dysbiosis and CSF biomarkers of amyloidosis, but not for tau. Further modeling is needed to establish the direct link between oral bacteria and Aβ

Intrinsic Subtype and Therapeutic Response Among HER2-Positive Breast Tumors from the NCCTG (Alliance) N9831 Trial.

Background: Genomic data from human epidermal growth factor receptor 2-positive (HER2+) tumors were analyzed to assess the association between intrinsic subtype and clinical outcome in a large, well-annotated patient cohort. Methods: Samples from the NCCTG (Alliance) N9831 trial were analyzed using the Prosigna algorithm on the NanoString platform to define intrinsic subtype, risk of recurrence scores, and risk categories for 1392 HER2+ tumors. Subtypes were evaluated for recurrence-free survival (RFS) using Kaplan-Meier and Cox model analysis following adjuvant chemotherapy (n = 484) or chemotherapy plus trastuzumab (n = 908). All statistical tests were two-sided. Results: Patients with HER2+ tumors from N9831 were primarily scored as HER2-enriched (72.1%). These individuals received statistically significant benefit from trastuzumab (hazard ratio [HR] = 0.68, 95% confidence interval [CI] = 0.52 to 0.89, P = .005), as did the patients (291 of 1392) with luminal-type tumors (HR = 0.52, 95% CI = 0.32 to 0.85, P = .01). Patients with basal-like tumors (97 of 1392) did not have statistically significantly better RFS when treated with trastuzumab and chemotherapy compared with chemotherapy alone (HR = 1.06, 95% CI = 0.53 to 2.13, P = .87). Conclusions: The majority of clinically defined HER2-positive tumors were classified as HER2-enriched or luminal using the Prosigna algorithm. Intrinsic subtype alone cannot replace conventional histopathological evaluation of HER2 status because many tumors that are classified as luminal A or luminal B will benefit from adjuvant trastuzumab if that subtype is accompanied by HER2 overexpression. However, among tumors that overexpress HER2, we speculate that assessment of intrinsic subtype may influence treatment, particularly with respect to evaluating alternative therapeutic approaches for that subset of HER2-positive tumors of the basal-like subtype

The relationship between quantitative human epidermal growth factor receptor 2 gene expression by the 21-gene reverse transcriptase polymerase chain reaction assay and adjuvant trastuzumab benefit in Alliance N9831

Introduction: The N9831 trial demonstrated the efficacy of adjuvant trastuzumab for patients with human epidermal growth factor receptor 2 (HER2) locally positive tumors by protein or gene analysis. We used the 21-gene assay to examine the association of quantitative HER2 messenger RNA (mRNA) gene expression and benefit from trastuzumab. Methods: N9831 tested the addition of trastuzumab to chemotherapy in stage I-III HER2-positive breast cancer. For two of the arms of the trial, doxorubicin and cyclophosphamide followed by paclitaxel (AC-T) and doxorubicin and cyclophosphamide followed by paclitaxel and trastuzumab concurrent chemotherapy-trastuzumab (AC-TH), recurrence score (RS) and HER2 mRNA expression were determined by the 21-gene assay (Oncotype DX®) (negative 2 expression units). Cox regression was used to assess the association of HER2 expression with trastuzumab benefit in preventing distant recurrence. Results: Median follow-up was 7.4years. Of 1,940 total patients, 901 had consent and sufficient tissue. HER2 by reverse transcriptase polymerase chain reaction (RT-PCR) was negative in 130 (14%), equivocal in 85 (9%), and positive in 686 (76%) patients. Concordance between HER2 assessments was 95% for RT-PCR versus central immunohistochemistry (IHC) (>10% positive cells = positive), 91% for RT-PCR versus central fluorescence in situ hybridization (FISH) (≥2.0 = positive) and 94% for central IHC versus central FISH. In the primary analysis, the association of HER2 expression by 21-gene assay with trastuzumab benefit was marginally nonsignificant (nonlinear p = 0.057). In hormone receptor-positive patients (local IHC) the association was significant (p = 0.002). The association was nonlinear with the greatest estimated benefit at lower and higher HER2 expression levels. Conclusions: Concordance among HER2 assessments by central IHC, FISH, and RT-PCR were similar and high. Association of HER2 mRNA expression with trastuzumab benefit as measured by time to distant recurrence was nonsignificant. A consistent benefit of trastuzumab irrespective of mHER2 levels was observed in patients with either IHC-positive or FISH-positive tumors. Trend for benefit was observed also for the small groups of patients with negative results by any or all of the central assays. Trial registration: Clinicaltrials.gov NCT00005970. Registered 5 July 2000

BABAR: an R package to simplify the normalisation of common reference design microarray-based transcriptomic datasets

Background: The development of DNA microarrays has facilitated the generation of hundreds of thousands of transcriptomic datasets. The use of a common reference microarray design allows existing transcriptomic data to be readily compared and re-analysed in the light of new data, and the combination of this design with large datasets is ideal for 'systems' level analyses. One issue is that these datasets are typically collected over many years and may be heterogeneous in nature, containing different microarray file formats and gene array layouts, dye-swaps, and showing varying scales of log(2)- ratios of expression between microarrays. Excellent software exists for the normalisation and analysis of microarray data but many data have yet to be analysed as existing methods struggle with heterogeneous datasets; options include normalising microarrays on an individual or experimental group basis. Our solution was to develop the Batch Anti-Banana Algorithm in R (BABAR) algorithm and software package which uses cyclic loess to normalise across the complete dataset. We have already used BABAR to analyse the function of Salmonella genes involved in the process of infection of mammalian cells. Results: The only input required by BABAR is unprocessed GenePix or BlueFuse microarray data files. BABAR provides a combination of 'within' and 'between' microarray normalisation steps and diagnostic boxplots. When applied to a real heterogeneous dataset, BABAR normalised the dataset to produce a comparable scaling between the microarrays, with the microarray data in excellent agreement with RT-PCR analysis. When applied to a real non-heterogeneous dataset and a simulated dataset, BABAR's performance in identifying differentially expressed genes showed some benefits over standard techniques. Conclusions: BABAR is an easy-to-use software tool, simplifying the simultaneous normalisation of heterogeneous two-colour common reference design cDNA microarray-based transcriptomic datasets. We show BABAR transforms real and simulated datasets to allow for the correct interpretation of these data, and is the ideal tool to facilitate the identification of differentially expressed genes or network inference analysis from transcriptomic datasets

Recursive regularization for inferring gene networks from time-course gene expression profiles

<p>Abstract</p> <p>Background</p> <p>Inferring gene networks from time-course microarray experiments with vector autoregressive (VAR) model is the process of identifying functional associations between genes through multivariate time series. This problem can be cast as a variable selection problem in Statistics. One of the promising methods for variable selection is the elastic net proposed by Zou and Hastie (2005). However, VAR modeling with the elastic net succeeds in increasing the number of true positives while it also results in increasing the number of false positives.</p> <p>Results</p> <p>By incorporating relative importance of the VAR coefficients into the elastic net, we propose a new class of regularization, called recursive elastic net, to increase the capability of the elastic net and estimate gene networks based on the VAR model. The recursive elastic net can reduce the number of false positives gradually by updating the importance. Numerical simulations and comparisons demonstrate that the proposed method succeeds in reducing the number of false positives drastically while keeping the high number of true positives in the network inference and achieves two or more times higher true discovery rate (the proportion of true positives among the selected edges) than the competing methods even when the number of time points is small. We also compared our method with various reverse-engineering algorithms on experimental data of MCF-7 breast cancer cells stimulated with two ErbB ligands, EGF and HRG.</p> <p>Conclusion</p> <p>The recursive elastic net is a powerful tool for inferring gene networks from time-course gene expression profiles.</p

A Tissue Biomarker Panel Predicting Systemic Progression after PSA Recurrence Post-Definitive Prostate Cancer Therapy

Many men develop a rising PSA after initial therapy for prostate cancer. While some of these men will develop a local or metastatic recurrence that warrants further therapy, others will have no evidence of disease progression. We hypothesized that an expression biomarker panel can predict which men with a rising PSA would benefit from further therapy.A case-control design was used to test the association of gene expression with outcome. Systemic (SYS) progression cases were men post-prostatectomy who developed systemic progression within 5 years after PSA recurrence. PSA progression controls were matched men post-prostatectomy with PSA recurrence but no evidence of clinical progression within 5 years. Using expression arrays optimized for paraffin-embedded tissue RNA, 1021 cancer-related genes were evaluated-including 570 genes implicated in prostate cancer progression. Genes from 8 previously reported marker panels were included. A systemic progression model containing 17 genes was developed. This model generated an AUC of 0.88 (95% CI: 0.84-0.92). Similar AUCs were generated using 3 previously reported panels. In secondary analyses, the model predicted the endpoints of prostate cancer death (in SYS cases) and systemic progression beyond 5 years (in PSA controls) with hazard ratios 2.5 and 4.7, respectively (log-rank p-values of 0.0007 and 0.0005). Genes mapped to 8q24 were significantly enriched in the model.Specific gene expression patterns are significantly associated with systemic progression after PSA recurrence. The measurement of gene expression pattern may be useful for determining which men may benefit from additional therapy after PSA recurrence

Impact of therapy on quality of life, neurocognitive function and their correlates in glioblastoma multiforme: a review

The maintenance of quality of life (QoL) in patients with high-grade glioma is an important endpoint during treatment, particularly in those with glioblastoma multiforme (GBM) given its dismal prognosis despite limited advances in standard therapy. It has proven difficult to identify new therapies that extend survival in patients with recurrent GBM, so one of the primary aims of new therapies is to reduce morbidity, restore or preserve neurologic functions, and the capacity to perform daily activities. Apart from temozolomide, cytotoxic chemotherapeutic agents do not appear to significantly impact response or survival, but produce toxicity that is likely to negatively impact QoL. New biological agents, such as bevacizumab, can induce a clinically meaningful proportion of durable responses among patients with recurrent GBM with an acceptable safety profile. Emerging evidence suggests that bevacizumab produces an improvement or preservation of neurocognitive function in GBM patients, suggestive of QoL improvement, in most poor-prognosis patients who would otherwise be expected to show a sudden and rapid deterioration in QoL

Evaluation of a new high-dimensional miRNA profiling platform

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are a class of approximately 22 nucleotide long, widely expressed RNA molecules that play important regulatory roles in eukaryotes. To investigate miRNA function, it is essential that methods to quantify their expression levels be available.</p> <p>Methods</p> <p>We evaluated a new miRNA profiling platform that utilizes Illumina's existing robust DASL chemistry as the basis for the assay. Using total RNA from five colon cancer patients and four cell lines, we evaluated the reproducibility of miRNA expression levels across replicates and with varying amounts of input RNA. The beta test version was comprised of 735 miRNA targets of Illumina's miRNA profiling application.</p> <p>Results</p> <p>Reproducibility between sample replicates within a plate was good (Spearman's correlation 0.91 to 0.98) as was the plate-to-plate reproducibility replicates run on different days (Spearman's correlation 0.84 to 0.98). To determine whether quality data could be obtained from a broad range of input RNA, data obtained from amounts ranging from 25 ng to 800 ng were compared to those obtained at 200 ng. No effect across the range of RNA input was observed.</p> <p>Conclusion</p> <p>These results indicate that very small amounts of starting material are sufficient to allow sensitive miRNA profiling using the Illumina miRNA high-dimensional platform. Nonlinear biases were observed between replicates, indicating the need for abundance-dependent normalization. Overall, the performance characteristics of the Illumina miRNA profiling system were excellent.</p

Multicentre phase II studies evaluating imatinib plus hydroxyurea in patients with progressive glioblastoma

Contains fulltext : 79699.pdf (publisher's version ) (Closed access)BACKGROUND: We evaluated the efficacy of imatinib mesylate in addition to hydroxyurea in patients with recurrent glioblastoma (GBM) who were either on or not on enzyme-inducing anti-epileptic drugs (EIAEDs). METHODS: A total of 231 patients with GBM at first recurrence from 21 institutions in 10 countries were enrolled. All patients received 500 mg of hydroxyurea twice a day. Imatinib was administered at 600 mg per day for patients not on EIAEDs and at 500 mg twice a day if on EIAEDs. The primary end point was radiographic response rate and secondary end points were safety, progression-free survival at 6 months (PFS-6), and overall survival (OS). RESULTS: The radiographic response rate after centralised review was 3.4%. Progression-free survival at 6 months and median OS were 10.6% and 26.0 weeks, respectively. Outcome did not appear to differ based on EIAED status. The most common grade 3 or greater adverse events were fatigue (7%), neutropaenia (7%), and thrombocytopaenia (7%). CONCLUSIONS: Imatinib in addition to hydroxyurea was well tolerated among patients with recurrent GBM but did not show clinically meaningful anti-tumour activity