Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets

<p>Abstract</p> <p>Background</p> <p>Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles from publicly available microarray datasets of cancer (breast, lymphoma and renal) samples linked to clinical information with an iterative machine learning algorithm. ROC curves were used to assess the prediction error of each profile for classification. We compared the prediction error of profiles correlated with molecular phenotype against profiles correlated with relapse-free status. Prediction error of profiles identified with supervised univariate feature selection algorithms were compared to profiles selected randomly from a) all genes on the microarray platform and b) a list of known disease-related genes (a priori selection). We also determined the relevance of expression profiles on test arrays from independent datasets, measured on either the same or different microarray platforms.</p> <p>Results</p> <p>Highly discriminative expression profiles were produced on both simulated gene expression data and expression data from breast cancer and lymphoma datasets on the basis of ER and BCL-6 expression, respectively. Use of relapse-free status to identify profiles for prognosis prediction resulted in poorly discriminative decision rules. Supervised feature selection resulted in more accurate classifications than random or a priori selection, however, the difference in prediction error decreased as the number of features increased. These results held when decision rules were applied across-datasets to samples profiled on the same microarray platform.</p> <p>Conclusion</p> <p>Our results show that many gene sets predict molecular phenotypes accurately. Given this, expression profiles identified using different training datasets should be expected to show little agreement. In addition, we demonstrate the difficulty in predicting relapse directly from microarray data using supervised machine learning approaches. These findings are relevant to the use of molecular profiling for the identification of candidate biomarker panels.</p

AAPT Diagnostic Criteria for Chronic Sickle Cell Disease Pain

Pain in sickle cell disease (SCD) is associated with increased morbidity, mortality, and high health care costs. Although episodic acute pain is the hallmark of this disorder, there is an increasing awareness that chronic pain is part of the pain experience of many older adolescents and adults. A common set of criteria for classifying chronic pain associated with SCD would enhance SCD pain research efforts in epidemiology, pain mechanisms, and clinical trials of pain management interventions, and ultimately improve clinical assessment and management. As part of the collaborative effort between the Analgesic, Anesthetic, and Addiction Clinical Trial Translations Innovations Opportunities and Networks public-private partnership with the U.S. Food and Drug Administration and the American Pain Society, the Analgesic, Anesthetic, and Addiction Clinical Trial Translations Innovations Opportunities and Networks-American Pain Society Pain Taxonomy initiative developed the outline of an optimal diagnostic system for chronic pain conditions. Subsequently, a working group of experts in SCD pain was convened to generate core diagnostic criteria for chronic pain associated with SCD. The working group synthesized available literature to provide evidence for the dimensions of this disease-specific pain taxonomy. A single pain condition labeled chronic SCD pain was derived with 3 modifiers reflecting different clinical features. Future systematic research is needed to evaluate the feasibility, validity, and reliability of these criteria. Perspective: An evidence-based classification system for chronic SCD pain was constructed for the Analgesic, Anesthetic, and Addiction Clinical Trial Translations Innovations Opportunities and Networks-American Pain Society Pain Taxonomy initiative. Applying this taxonomy may improve assessment and management of SCD pain and accelerate research on epidemiology, mechanisms, and treatments for chronic SCD pain

Cyclin D1 integrates G9a-mediated histone methylation.

Lysine methylation of histones and non-histone substrates by the SET domain containing protein lysine methyltransferase (KMT) G9a/EHMT2 governs transcription contributing to apoptosis, aberrant cell growth, and pluripotency. The positioning of chromosomes within the nuclear three-dimensional space involves interactions between nuclear lamina (NL) and the lamina-associated domains (LAD). Contact of individual LADs with the NL are dependent upon H3K9me2 introduced by G9a. The mechanisms governing the recruitment of G9a to distinct subcellular sites, into chromatin or to LAD, is not known. The cyclin D1 gene product encodes the regulatory subunit of the holoenzyme that phosphorylates pRB and NRF1 thereby governing cell-cycle progression and mitochondrial metabolism. Herein, we show that cyclin D1 enhanced H3K9 dimethylation though direct association with G9a. Endogenous cyclin D1 was required for the recruitment of G9a to target genes in chromatin, for G9a-induced H3K9me2 of histones, and for NL-LAD interaction. The finding that cyclin D1 is required for recruitment of G9a to target genes in chromatin and for H3K9 dimethylation, identifies a novel mechanism coordinating protein methylation

Kinase-independent role of cyclin D1 in chromosomal instability and mammary tumorigenesis

Cyclin D1 is an important molecular driver of human breast cancer but better understanding of its oncogenic mechanisms is needed, especially to enhance efforts in targeted therapeutics. Currently, pharmaceutical initiatives to inhibit cyclin D1 are focused on the catalytic component since the transforming capacity is thought to reside in the cyclin D1/CDK activity. We initiated the following study to directly test the oncogenic potential of catalytically inactive cyclin D1 in an in vivo mouse model that is relevant to breast cancer. Herein, transduction of cyclin D1(-/-) mouse embryonic fibroblasts (MEFs) with the kinase dead KE mutant of cyclin D1 led to aneuploidy, abnormalities in mitotic spindle formation, autosome amplification, and chromosomal instability (CIN) by gene expression profiling. Acute transgenic expression of either cyclin D1(WT) or cyclin D1(KE) in the mammary gland was sufficient to induce a high CIN score within 7 days. Sustained expression of cyclin D1(KE) induced mammary adenocarcinoma with similar kinetics to that of the wild-type cyclin D1. ChIP-Seq studies demonstrated recruitment of cyclin D1(WT) and cyclin D1(KE) to the genes governing CIN. We conclude that the CDK-activating function of cyclin D1 is not necessary to induce either chromosomal instability or mammary tumorigenesis

Preclinical episodes of orofacial pain symptoms and their association with health care behaviors in the OPPERA prospective cohort study

The course of preclinical pain symptoms sheds light on the etiology and prognosis of chronic pain. We aimed to quantify rates of developing initial- and recurrent-symptoms of painful temporomandibular disorder (TMD) and to evaluate associations with health behaviors. In the OPPERA prospective cohort study, 2,719 people aged 18-44 years with lifetime absence of TMD when enrolled completed 25,103 quarterly (three-monthly) questionnaires during amedian 2.3-year follow-up period. Questionnaires documented TMD symptom episodes, headache, other body pain, health care attendance and analgesic usage and. Kaplan-Meier methods for clustered data estimated symptom-free survival time. Multivariable models assessed demographic variation in TMD symptom rates and evaluated associations with healthcare and analgesic use. One third of people developed TMD symptoms and for one quarter of symptomatic episodes, pain intensity was severe. Initial TMD symptoms developed at anannual rate of 18.8 episodes per 100 people. The annual rate more than doubled for first-recurrence and doubled again for second-or-subsequent recurrence such that, one year after first recurrence, 71% of people experienced second recurrence. The overall rate increased with age and was greater in African-Americans and lower in Asians relative to Whites. The probability of TMD symptoms was strongly associated with concurrent episodes of headache and body pain and with past episodes of TMD symptoms. Episodes of TMD symptoms, headache and body pain were associated with increases of ~10% in probability of analgesic usage and healthcare attendance. Yet, even when TMD, headache and body pain occurred concurrently, 27% of people neither attended healthcare nor used analgesics

Prediction of HIV-1 virus-host protein interactions using virus and host sequence motifs

<p>Abstract</p> <p>Background</p> <p>Host protein-protein interaction networks are altered by invading virus proteins, which create new interactions, and modify or destroy others. The resulting network topology favors excessive amounts of virus production in a stressed host cell network. Short linear peptide motifs common to both virus and host provide the basis for host network modification.</p> <p>Methods</p> <p>We focused our host-pathogen study on the binding and competing interactions of HIV-1 and human proteins. We showed that peptide motifs conserved across 70% of HIV-1 subtype B and C samples occurred in similar positions on HIV-1 proteins, and we documented protein domains that interact with these conserved motifs. We predicted which human proteins may be targeted by HIV-1 by taking pairs of human proteins that may interact via a motif conserved in HIV-1 and the corresponding interacting protein domain.</p> <p>Results</p> <p>Our predictions were enriched with host proteins known to interact with HIV-1 proteins ENV, NEF, and TAT (p-value < 4.26E-21). Cellular pathways statistically enriched for our predictions include the T cell receptor signaling, natural killer cell mediated cytotoxicity, cell cycle, and apoptosis pathways. Gene Ontology molecular function level 5 categories enriched with both predicted and confirmed HIV-1 targeted proteins included categories associated with phosphorylation events and adenyl ribonucleotide binding.</p> <p>Conclusion</p> <p>A list of host proteins highly enriched with those targeted by HIV-1 proteins can be obtained by searching for host protein motifs along virus protein sequences. The resulting set of host proteins predicted to be targeted by virus proteins will become more accurate with better annotations of motifs and domains. Nevertheless, our study validates the role of linear binding motifs shared by virus and host proteins as an important part of the crosstalk between virus and host.</p

Study Protocol, Sample Characteristics, and Loss to Follow-Up: The OPPERA Prospective Cohort Study

When studying incidence of pain conditions such as temporomandibular disorders (TMDs), repeated monitoring is needed in prospective cohort studies. However, monitoring methods usually have limitations and, over a period of years, some loss to follow-up is inevitable. The OPPERA prospective cohort study of first-onset TMD screened for symptoms using quarterly questionnaires and examined symptomatic participants to definitively ascertain TMD incidence. During the median 2.8-year observation period, 16% of the 3,263 enrollees completed no follow-up questionnaires, others provided incomplete follow-up, and examinations were not conducted for one third of symptomatic episodes. Although screening methods and examinations were found to have excellent reliability and validity, they were not perfect. Loss to follow-up varied according to some putative TMD risk factors, although multiple imputation to correct the problem suggested that bias was minimal. A second method of multiple imputation that evaluated bias associated with omitted and dubious examinations revealed a slight underestimate of incidence and some small biases in hazard ratios used to quantify effects of risk factors. Although “bottom line” statistical conclusions were not affected, multiply-imputed estimates should be considered when evaluating the large number of risk factors under investigation in the OPPERA study

Study Methods, Recruitment, Sociodemographic Findings, and Demographic Representativeness in the OPPERA Study

This paper describes methods used in the project “Orofacial Pain Prospective Evaluation and Risk Assessment” (OPPERA) and evaluates socio-demographic characteristics associated with temporomandibular disorders (TMD) in the OPPERA case-control study. Representativeness was investigated by comparing socio-demographic profiles of OPPERA participants with population census profiles of counties near study sites and by comparing age- and gender-associations with TMD in OPPERA and the 2007-09 US National Health Interview Survey. Volunteers aged 18-44 years were recruited at four US study sites: 3,263 people without TMD were enrolled into the prospective cohort study; 1,633 of them were selected as controls for the baseline case-control study. Cases were 185 volunteers with examiner-classified TMD. Distributions of some demographic characteristics among OPPERA participants differed from census profiles, although there was less difference in socio-economic profiles. Odds of TMD was associated with greater age in this 18-44 year range; females had three times the odds of TMD as males; and relative to non-Hispanic-Whites, other racial groups had one-fifth the odds of TMD. Age- and gender-associations with chronic TMD were strikingly similar to associations observed in the US population. Assessments of representativeness in this demographically diverse group of community volunteers suggest that OPPERA case-control findings have good internal validity

Host sequence motifs shared by HIV predict response to antiretroviral therapy

<p>Abstract</p> <p>Background</p> <p>The HIV viral genome mutates at a high rate and poses a significant long term health risk even in the presence of combination antiretroviral therapy. Current methods for predicting a patient's response to therapy rely on site-directed mutagenesis experiments and <it>in vitro </it>resistance assays. In this bioinformatics study we treat response to antiretroviral therapy as a two-body problem: response to therapy is considered to be a function of both the host and pathogen proteomes. We set out to identify potential responders based on the presence or absence of host protein and DNA motifs on the HIV proteome.</p> <p>Results</p> <p>An alignment of thousands of HIV-1 sequences attested to extensive variation in nucleotide sequence but also showed conservation of eukaryotic short linear motifs on the protein coding regions. The reduction in viral load of patients in the Stanford HIV Drug Resistance Database exhibited a bimodal distribution after 24 weeks of antiretroviral therapy, with 2,000 copies/ml cutoff. Similarly, patients allocated into responder/non-responder categories based on consistent viral load reduction during a 24 week period showed clear separation. In both cases of phenotype identification, a set of features composed of short linear motifs in the reverse transcriptase region of HIV sequence accurately predicted a patient's response to therapy. Motifs that overlap resistance sites were highly predictive of responder identification in single drug regimens but these features lost importance in defining responders in multi-drug therapies.</p> <p>Conclusion</p> <p>HIV sequence mutates in a way that preferentially preserves peptide sequence motifs that are also found in the human proteome. The presence and absence of such motifs at specific regions of the HIV sequence is highly predictive of response to therapy. Some of these predictive motifs overlap with known HIV-1 resistance sites. These motifs are well established in bioinformatics databases and hence do not require identification via <it>in vitro </it>mutation experiments.</p