Genomic screening methodology not requiring barcoding: Single nucleotide polymorphism-based, mixed-cell screening (SMICS).

Although high-throughput, cancer cell-line screening is a time-honored, important tool for anti-cancer drug development, this process involves the testing of each, individual drug in each, individual cell-line. Despite the availability of robotic liquid handling systems, this process remains a time-consuming and costly investment. The Broad Institute developed a new method called Profiling Relative Inhibition Simultaneously in Mixtures (PRISM) to screen a mixture of barcoded, tumor cell-lines. Although this methodology significantly improved the efficiency of screening large numbers of cell-lines, the barcoding process itself was tedious that requires gene transfection and subsequent selection of stable cell-lines. In this study, we developed a new, genomic approach for screening multiple cancer cell-lines using endogenous "tags" that did not require prior barcoding: single nucleotide polymorphism-based, mixed-cell screening (SMICS). The code for SMICS is available at https://github.com/MarkeyBBSRF/SMICS.

Bayesian kinetic modeling for tracer-based metabolomic data.

BACKGROUND: Stable Isotope Resolved Metabolomics (SIRM) is a new biological approach that uses stable isotope tracers such as uniformly [Formula: see text]-enriched glucose ([Formula: see text]-Glc) to trace metabolic pathways or networks at the atomic level in complex biological systems. Non-steady-state kinetic modeling based on SIRM data uses sets of simultaneous ordinary differential equations (ODEs) to quantitatively characterize the dynamic behavior of metabolic networks. It has been increasingly used to understand the regulation of normal metabolism and dysregulation in the development of diseases. However, fitting a kinetic model is challenging because there are usually multiple sets of parameter values that fit the data equally well, especially for large-scale kinetic models. In addition, there is a lack of statistically rigorous methods to compare kinetic model parameters between different experimental groups. RESULTS: We propose a new Bayesian statistical framework to enhance parameter estimation and hypothesis testing for non-steady-state kinetic modeling of SIRM data. For estimating kinetic model parameters, we leverage the prior distribution not only to allow incorporation of experts' knowledge but also to provide robust parameter estimation. We also introduce a shrinkage approach for borrowing information across the ensemble of metabolites to stably estimate the variance of an individual isotopomer. In addition, we use a component-wise adaptive Metropolis algorithm with delayed rejection to perform efficient Monte Carlo sampling of the posterior distribution over high-dimensional parameter space. For comparing kinetic model parameters between experimental groups, we propose a new reparameterization method that converts the complex hypothesis testing problem into a more tractable parameter estimation problem. We also propose an inference procedure based on credible interval and credible value. Our method is freely available for academic use at https://github.com/xuzhang0131/MCMCFlux . CONCLUSIONS: Our new Bayesian framework provides robust estimation of kinetic model parameters and enables rigorous comparison of model parameters between experimental groups. Simulation studies and application to a lung cancer study demonstrate that our framework performs well for non-steady-state kinetic modeling of SIRM data.

Visceral fat-specific regulation of plasminogen activator inhibitor-1 in aged septic mice.

Elevated plasma levels of plasminogen activator inhibitor-1 (PAI-1) are documented in patients with sepsis and levels positively correlate with disease severity and mortality. Our previous work demonstrated that visceral adipose tissues (VAT) are a major source of PAI-1, especially in the aged (murine endotoxemia), that circulating PAI-1 protein levels match the trajectory of PAI-1 transcript levels in VAT (clinical sepsis), and that PAI-1 in both VAT and plasma are positively associated with acute kidney injury (AKI) in septic patients. In the current study utilizing preclinical sepsis models, PAI-1 tissue distribution was examined and cellular sources, as well as mechanisms mediating PAI-1 induction in VAT, were identified. In aged mice with sepsis, PAI-1 gene expression was significantly higher in VAT than in other major organs. VAT PAI-1 gene expression correlated with PAI-1 protein levels in both VAT and plasma. Moreover, VAT and plasma levels of PAI-1 were positively associated with AKI markers, modeling our previous clinical data. Using explant cultures of VAT, we determined that PAI-1 is secreted robustly in response to recombinant transforming growth factor ß (TGFß) and tumor necrosis factor α (TNFα) treatment; however, neutralization was effective only for TNFα indicating that TGFß is not an endogenous modulator of PAI-1. Within VAT, TNFα was localized to neutrophils and macrophages. PAI-1 protein levels were fourfold higher in stromal vascular fraction (SVF) cells compared with mature adipocytes, and among SVF cells, both immune and nonimmune compartments expressed PAI-1 in a similar fashion. PAI-1 was localized predominantly to macrophages within the immune compartment and preadipocytes and endothelial cells within the nonimmune compartment. Collectively, these results indicate that induction and secretion of PAI-1 from VAT is facilitated by a complex interaction among immune and nonimmune cells. As circulating PAI-1 contributes to AKI in sepsis, understanding PAI-1 regulation in VAT could yield novel strategies for reducing systemic consequences of PAI-1 overproduction.

MEScan: a powerful statistical framework for genome-scale mutual exclusivity analysis of cancer mutations.

MOTIVATION: Cancer somatic driver mutations associated with genes within a pathway often show a mutually exclusive pattern across a cohort of patients. This mutually exclusive mutational signal has been frequently used to distinguish driver from passenger mutations and to investigate relationships among driver mutations. Current methods for de novo discovery of mutually exclusive mutational patterns are limited because the heterogeneity in background mutation rate can confound mutational patterns, and the presence of highly mutated genes can lead to spurious patterns. In addition, most methods only focus on a limited number of pre-selected genes and are unable to perform genome-wide analysis due to computational inefficiency. RESULTS: We introduce a statistical framework, MEScan, for accurate and efficient mutual exclusivity analysis at the genomic scale. Our framework contains a fast and powerful statistical test for mutual exclusivity with adjustment of the background mutation rate and impact of highly mutated genes, and a multi-step procedure for genome-wide screening with the control of false discovery rate. We demonstrate that MEScan more accurately identifies mutually exclusive gene sets than existing methods and is at least two orders of magnitude faster than most methods. By applying MEScan to data from four different cancer types and pan-cancer, we have identified several biologically meaningful mutually exclusive gene sets. AVAILABILITY AND IMPLEMENTATION: MEScan is available as an R package at https://github.com/MarkeyBBSRF/MEScan. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Use of Wearable Sensors to Assess the Effects of Performing a Cognitive Task on Sensory Integration of Balance in Healthy Individuals.

This study investigated the effects of performing a cognitive task on the sensory integration of balance in healthy individuals. Ten subjects (five F/five M; 21.5 ± 2.17 years; 69.9 ± 3.4 inches; 155.6 ± 26.1 lbs; Caucasian), without known balance issues, performed the modified Clinical Test of Sensory Interaction of Balance (mCTSIB) with and without a cognitive task. The cognitive task involved counting down in threes from a randomly assigned number between 95 and 100. Postural sway area and postural sway jerk were assessed through the use of inertial sensors placed around the subjects' lower lumbar region. Each subject performed four trials for the four conditions of the mCTSIB: eyes open firm (EOFirm), eyes closed firm (ECFirm), eyes open foam (EOFoam), and eyes closed foam (ECFoam). We tested the effect of performing a cognitive task on the sensory integration of balance. We hypothesized that sensory cognitive interaction would be more apparent for more complex conditions and would be better assessed with postural sway jerk compared to postural sway area measure. With the addition of a cognitive task for the mCTSIB: (1) postural sway area increased in the baseline condition, i.e., EOFirm (p < 0.05), but did not increase in the most difficult condition, i.e., ECFoam; (2) postural sway jerk increased in all conditions of the mCTSIB (p < 0.05); (3) cognitive performance did not deteriorate across conditions of the mCTSIB. Postural sway jerk was shown to be a more sensitive measure in detecting the effect of a cognitive task on sensory integration for postural control. Overall, inertial sensors can be used to reliably assess postural sway differences related to sensory−cognitive integration.

Gingival tissue autophagy pathway gene expression profiles in periodontitis and aging.

OBJECTIVE: We hypothesized that autophagy-related genes will be differentially expressed in periodontitis, suggesting an impaired gingival autophagic response associated with disease. BACKGROUND: Autophagy is a cellular physiologic mechanism to maintain tissue homeostasis, while deficient autophagic responses increase inflammation and susceptibility to infection. METHODS: Rhesus monkeys [<3 years to 23 years of age (n = 34)] were examined for periodontal health and naturally occurring periodontitis. Gingival tissues samples were obtained from healthy or diseased sites, total RNA was isolated, and the Rhesus Gene Chip 1.0 ST (Affymetrix) was used for gene expression analysis of 150 autophagy-related genes. RESULTS: Comparison of expression levels with adult healthy tissues demonstrated a rather limited number of individual genes that were significantly different across the age-groups. In contrast, with periodontitis in the adults and aged animals, about 15% of the genes were significantly increased or decreased. The differences were reflected in the mTOR complex (5/12), ULK1/ATG1 complex (5/9), PI3K complex (5/21), ATG9 complex (2/7), ATG12 conjugation/LC3 lipidation (7/22), and lysosome fusion/vesicle degradation [LF/VD (5/10)] activities within the broader autophagic pathway. The genes most greatly altered in gingival tissues of naturally occurring periodontitis were identified in the ATG12 and LF/VD pathways that approximated 50% of the genes in each of those categories. While healthy gingival aging did not appear to reflect altered autophagy gene expression, substantial differences were noted with periodontitis irrespective of the age of the animals. Future studies into the role of autophagy in periodontitis and could offer potential new therapeutic strategies to prevent and/or treat periodontal disease.

Identifying factors impacting the efficacy of postmastectomy radiotherapy in patients with early-stage breast cancer and one to two positive lymph nodes.

INTRODUCTION: In women with T1-2 breast cancer and one to two positive axillary lymph nodes (LN) at low risk for recurrence, postmastectomy radiation therapy (PMRT) may provide insufficient benefit to justify its toxicity. This study evaluated the interaction of factors associated with overall survival (OS) after PMRT in these patients. METHODS: The National Cancer Database was queried for women with T1-2 breast cancer undergoing mastectomy with one to two positive LN identified on lymphadenectomy. Patients were grouped according to number of positive LN and then stratified by PMRT use. Differences in OS were evaluated. RESULTS: Multivariable modeling demonstrated an interaction effect of age on the efficacy of PMRT. In patients more than or equal to 60 years old, PMRT was associated with improved survival when adjusting for age and tumor grade in patients with 1 to 2 positive LN (risk ratio = 0.62, 95% confidence interval = 0.40-0.93, P = .018). In patients less than 60 years old, tumor size and grade, but not PMRT, were associated with improved OS. CONCLUSION: For women with T1-2 breast cancer and one to two positive LN, PMRT's association with OS is influenced by age, tumor grade, and number of positive LN. PMRT appears to be associated with improvements in OS in older patients, but not younger patients, regardless of tumor size or nodal status.

The Effect of Personal Protective Equipment on Firefighter Occupational Performance.

Lesniak, AY, Bergstrom, HC, Clasey, JL, Stromberg, AJ, and Abel, MG. The effect of personal protective equipment on firefighter occupational performance. J Strength Cond Res 34(8): 2165-2172, 2020-The purpose of this study was to evaluate the effects of load carriage (LC) and LC plus respirator use (LC + self-contained breathing apparatus [SCBA]) on firefighters' work capacity to enhance our understanding of occupational demands. Twenty-one male structural firefighter recruits (age: 28.6 ± 4.3 years; height: 178.6 ± 7.2 cm; body mass: 94.1 ± 15.4 kg; body fat: 22.9 ± 6.1%) participated. Occupational performance was assessed by time to complete a simulated fire ground test (SFGT). After 2 familiarization trials, recruits performed the following SFGT conditions in a randomized order: PT (physical training clothes), LC only, and LC + SCBA. To describe within-group differences between SFGT conditions, relative difference scores were calculated as follows: % difference = ([experimental trial outcome - PT trial outcome]/PT trial outcome) × 100. Statistical differences between conditions were assessed with repeated-measures analysis of variance. The level of significance was set p < 0.01. Time to complete the LC + SCBA trial (345.9 ± 43.7 seconds; p < 0.001) and LC-only trial (331.2 ± 39.3 seconds; p < 0.001) were significantly greater than the PT trial (241.0 ± 33.3 seconds). Post-SFGT rating of perceived exertion was higher in the LC + SCBA trial (6.7 ± 1.7) and LC trial (6.4 ± 1.5) compared with the PT trial (4.7 ± 1.8; p < 0.001). Heart rate and lactate measures were similar across conditions (p = 0.488; p = 0.287). Personal protective equipment (PPE) significantly decreases the work capacity and increases the perceived effort of occupational tasks. Thus, these findings describe the additional physical demands produced by PPE and indicate that performance of firefighting tasks in an unloaded condition does not reflect work capacity in a bona fide condition.

A probabilistic method for leveraging functional annotations to enhance estimation of the temporal order of pathway mutations during carcinogenesis.

BACKGROUND: Cancer arises through accumulation of somatically acquired genetic mutations. An important question is to delineate the temporal order of somatic mutations during carcinogenesis, which contributes to better understanding of cancer biology and facilitates identification of new therapeutic targets. Although a number of statistical and computational methods have been proposed to estimate the temporal order of mutations, they do not account for the differences in the functional impacts of mutations and thus are likely to be obscured by the presence of passenger mutations that do not contribute to cancer progression. In addition, many methods infer the order of mutations at the gene level, which have limited power due to the low mutation rate in most genes. RESULTS: In this paper, we develop a Probabilistic Approach for estimating the Temporal Order of Pathway mutations by leveraging functional Annotations of mutations (PATOPA). PATOPA infers the order of mutations at the pathway level, wherein it uses a probabilistic method to characterize the likelihood of mutational events from different pathways occurring in a certain order. The functional impact of each mutation is incorporated to weigh more on a mutation that is more integral to tumor development. A maximum likelihood method is used to estimate parameters and infer the probability of one pathway being mutated prior to another. Simulation studies and analysis of whole exome sequencing data from The Cancer Genome Atlas (TCGA) demonstrate that PATOPA is able to accurately estimate the temporal order of pathway mutations and provides new biological insights on carcinogenesis of colorectal and lung cancers. CONCLUSIONS: PATOPA provides a useful tool to estimate temporal order of mutations at the pathway level while leveraging functional annotations of mutations.

SDA: a semi-parametric differential abundance analysis method for metabolomics and proteomics data.

BACKGROUND: Identifying differentially abundant features between different experimental groups is a common goal for many metabolomics and proteomics studies. However, analyzing data from mass spectrometry (MS) is difficult because the data may not be normally distributed and there is often a large fraction of zero values. Although several statistical methods have been proposed, they either require the data normality assumption or are inefficient. RESULTS: We propose a new semi-parametric differential abundance analysis (SDA) method for metabolomics and proteomics data from MS. The method considers a two-part model, a logistic regression for the zero proportion and a semi-parametric log-linear model for the possibly non-normally distributed non-zero values, to characterize data from each feature. A kernel-smoothed likelihood method is developed to estimate model coefficients and a likelihood ratio test is constructed for differential abundant analysis. The method has been implemented into an R package, SDAMS, which is available at https://www.bioconductor.org/packages/release/bioc/html/SDAMS.html . CONCLUSION: By introducing the two-part semi-parametric model, SDA is able to handle both non-normally distributed data and large fraction of zero values in a MS dataset. It also allows for adjustment of covariates. Simulations and real data analyses demonstrate that SDA outperforms existing methods.

Variability in Predictions from Online Tools: A Demonstration Using Internet-Based Melanoma Predictors.

BACKGROUND: Prognostic models are increasingly being made available online, where they can be publicly accessed by both patients and clinicians. These online tools are an important resource for patients to better understand their prognosis and for clinicians to make informed decisions about treatment and follow-up. The goal of this analysis was to highlight the possible variability in multiple online prognostic tools in a single disease. METHODS: To demonstrate the variability in survival predictions across online prognostic tools, we applied a single validation dataset to three online melanoma prognostic tools. Data on melanoma patients treated at Memorial Sloan Kettering Cancer Center between 2000 and 2014 were retrospectively collected. Calibration was assessed using calibration plots and discrimination was assessed using the C-index. RESULTS: In this demonstration project, we found important differences across the three models that led to variability in individual patients' predicted survival across the tools, especially in the lower range of predictions. In a validation test using a single-institution data set, calibration and discrimination varied across the three models. CONCLUSIONS: This study underscores the potential variability both within and across online tools, and highlights the importance of using methodological rigor when developing a prognostic model that will be made publicly available online. The results also reinforce that careful development and thoughtful interpretation, including understanding a given tool's limitations, are required in order for online prognostic tools that provide survival predictions to be a useful resource for both patients and clinicians.

A model for predicting low probability of nonsentinel lymph node positivity in melanoma patients with a single positive sentinel lymph node.

BACKGROUND: Identifying factors associated with nonsentinel lymph node (NSN) metastases in melanoma patients with a single positive sentinel lymph node (SLN) could aid decision making regarding adjuvant therapy. We describe a model for identifying patients with a single positive SLN at low risk for NSN metastasis. METHODS: Factors associated with NSN metastasis in patients with a primary cutaneous melanoma and a single positive SLN who underwent completion lymph node dissection (CLND) were identified. These factors were used to construct a model for predicting the NSN status. The model was validated using a separate data set from another tertiary referral cancer center. RESULTS: In the training data set, 111 patients had a single positive SLN. Of these, 27 had positive NSN. SLN tumor deposit diameter ≥0.75 mm (OR, 3.43; P = 0.047), age ≥40 (OR, 12.14; P = 0.024), and multifocal SLN tumor deposit location (OR, 4.16; P = 0.0096) were independently associated with NSN positivity. Patients with 0 to 1 of these risk factors had a low risk of NSN metastasis in both the training (7.5%) and validation (4.6%) data sets. CONCLUSIONS: A combination of patient and SLN tumor burden characteristics can help to identify patients with a single positive SLN who are at a low risk of NSN metastasis.

NanoStringDiff: a novel statistical method for differential expression analysis based on NanoString nCounter data.

The advanced medium-throughput NanoString nCounter technology has been increasingly used for mRNA or miRNA differential expression (DE) studies due to its advantages including direct measurement of molecule expression levels without amplification, digital readout and superior applicability to formalin fixed paraffin embedded samples. However, the analysis of nCounter data is hampered because most methods developed are based on t-tests, which do not fit the count data generated by the NanoString nCounter system. Furthermore, data normalization procedures of current methods are either not suitable for counts or not specific for NanoString nCounter data. We develop a novel DE detection method based on NanoString nCounter data. The method, named NanoStringDiff, considers a generalized linear model of the negative binomial family to characterize count data and allows for multifactor design. Data normalization is incorporated in the model framework through data normalization parameters, which are estimated from positive controls, negative controls and housekeeping genes embedded in the nCounter system. We propose an empirical Bayes shrinkage approach to estimate the dispersion parameter in the model and a likelihood ratio test to identify differentially expressed genes. Simulations and real data analysis demonstrate that the proposed method performs better than existing methods.

Differentiating gold nanorod samples using particle size and shape distributions from transmission electron microscope images.

Size and shape distributions of gold nanorod samples are critical to their physico-chemical properties, especially their longitudinal surface plasmon resonance. This interlaboratory comparison study developed methods for measuring and evaluating size and shape distributions for gold nanorod samples using transmission electron microscopy (TEM) images. The objective was to determine whether two different samples, which had different performance attributes in their application, were different with respect to their size and/or shape descriptor distributions. Touching particles in the captured images were identified using a ruggedness shape descriptor. Nanorods could be distinguished from nanocubes using an elongational shape descriptor. A non-parametric statistical test showed that cumulative distributions of an elongational shape descriptor, that is, the aspect ratio, were statistically different between the two samples for all laboratories. While the scale parameters of size and shape distributions were similar for both samples, the width parameters of size and shape distributions were statistically different. This protocol fulfills an important need for a standardized approach to measure gold nanorod size and shape distributions for applications in which quantitative measurements and comparisons are important. Furthermore, the validated protocol workflow can be automated, thus providing consistent and rapid measurements of nanorod size and shape distributions for researchers, regulatory agencies, and industry.

The Trophic Life Cycle Stage of the Opportunistic Fungal Pathogen Pneumocystis murina Hinders the Ability of Dendritic Cells To Stimulate CD4+ T Cell Responses.

The life cycle of the opportunistic fungal pathogen Pneumocystis murina consists of a trophic stage and an ascus-like cystic stage. Infection with the cyst stage induces proinflammatory immune responses, while trophic forms suppress the cytokine response to multiple pathogen-associated molecular patterns (PAMPs), including ß-glucan. A targeted gene expression assay was used to evaluate the dendritic cell response following stimulation with trophic forms alone, with a normal mixture of trophic forms and cysts, or with ß-glucan. We demonstrate that stimulation with trophic forms downregulated the expression of multiple genes normally associated with the response to infection, including genes encoding transcription factors. Trophic forms also suppressed the expression of genes related to antigen processing and presentation, including the gene encoding the major histocompatibility complex (MHC) class II transactivator, CIITA. Stimulation of dendritic cells with trophic forms, but not a mixture of trophic forms and cysts, reduced the expression of MHC class II and the costimulatory molecule CD40 on the surface of the cells. These defects in the expression of MHC class II and costimulatory molecules corresponded with a reduced capacity for trophic form-loaded dendritic cells to stimulate CD4+ T cell proliferation and polarization. These data are consistent with the delayed innate and adaptive responses previously observed in immunocompetent mice inoculated with trophic forms compared to responses in mice inoculated with a mixture of trophic forms and cysts. We propose that trophic forms broadly inhibit the ability of dendritic cells to fulfill their role as antigen-presenting cells.

Activity-Dependent Gene Expression in the Mammalian Olfactory Epithelium.

Activity-dependent processes are important to olfactory sensory neurons (OSNs) in several ways, such as cell survival and the specificity of axonal convergence. The identification of activity-dependent mRNAs has contributed to our understanding of OSN axon convergence, but has revealed surprisingly little about other processes. Published studies of activity-dependent mRNAs in olfactory mucosae overlap poorly, but by combining these agreements with meta-analysis of existing data we identify 443 mRNAs that respond to methods that alter OSN activity. Three hundred and fifty of them are expressed in mature OSNs, consistent with the expectation that activity-dependent responses are cell autonomous and driven by odor stimulation. Many of these mRNAs encode proteins that function at presynaptic terminals or support electrical activity, consistent with hypotheses linking activity dependence to synaptic plasticity and energy conservation. The lack of agreement between studies is due largely to underpowered experiments. In addition, methods used to alter OSN activity are susceptible to indirect or off-target effects. These effects deserve greater attention, not only to rigorously identify OSN mRNAs that respond to altered OSN activity, but also because these effects are of significant interest in their own right. For example, the mRNAs of some sustentacular cell enzymes believed to function in odorant clearance (Cyp2a4 and Cyp2g1) are sensitive to unilateral naris occlusion used to reduce odorant stimulation of the ipsilateral olfactory epithelium. Also problematic are odorant receptor mRNAs, which show little agreement across studies and are susceptible to differences in frequency of expression that masquerade as activity-dependent changes in mRNA abundance.

Secretory antibodies in breast milk promote long-term intestinal homeostasis by regulating the gut microbiota and host gene expression.

Maintenance of intestinal homeostasis requires a healthy relationship between the commensal gut microbiota and the host immune system. Breast milk supplies the first source of antigen-specific immune protection in the gastrointestinal tract of suckling mammals, in the form of secretory IgA (SIgA). SIgA is transported across glandular and mucosal epithelial cells into external secretions by the polymeric Ig receptor (pIgR). Here, a breeding scheme with polymeric Ig receptor-sufficient and -deficient mice was used to study the effects of breast milk-derived SIgA on development of the gut microbiota and host intestinal immunity. Early exposure to maternal SIgA prevented the translocation of aerobic bacteria from the neonatal gut into draining lymph nodes, including the opportunistic pathogen Ochrobactrum anthropi. By the age of weaning, mice that received maternal SIgA in breast milk had a significantly different gut microbiota from mice that did not receive SIgA, and these differences were magnified when the mice reached adulthood. Early exposure to SIgA in breast milk resulted in a pattern of intestinal epithelial cell gene expression in adult mice that differed from that of mice that were not exposed to passive SIgA, including genes associated with intestinal inflammatory diseases in humans. Maternal SIgA was also found to ameliorate colonic damage caused by the epithelial-disrupting agent dextran sulfate sodium. These findings reveal unique mechanisms through which SIgA in breast milk may promote lifelong intestinal homeostasis, and provide additional evidence for the benefits of breastfeeding.

Melanoma Patient-Reported Quality of Life Outcomes Following Sentinel Lymph Node Biopsy, Completion Lymphadenectomy, and Adjuvant Interferon: Results from the Sunbelt Melanoma Trial.

BACKGROUND: Quality of life (QOL) and physical condition (PC) outcomes after sentinel lymph node biopsy (SLNB), completion lymph node dissection (CLND), and adjuvant therapy with interferon alfa-2b (IFN) were evaluated in this study. METHODS: Self-reported QOL and PC scores were evaluated in patients enrolled in a prospective, multicenter, randomized, clinical trial evaluating adjuvant IFN. After SLN biopsy, patients with a positive SLN underwent CLND then were randomized to adjuvant IFN or observation. QOL and PC scores were compared between patients who underwent SLNB alone, CLND without IFN, and CLND with IFN. Time to return to baseline QOL and PC scores reported at the time of SLNB was recorded and compared. RESULTS: There were statistically significant differences in time to return to baseline QOL (p = 0.0018) and PC (p = 0.0018) scores across the three treatment groups. The time to return to baseline QOL and PC scores was similar for SLND and CLND alone. Differences in time to return to baseline QOL and PC were sustained when stratified by recurrence status but did not differ significantly for different lymph node regions. There was a delay in return to baseline QOL and PC condition scores that was sustained beyond the cessation of IFN therapy. CONCLUSIONS: CLND is well-tolerated with a similar effect on self-reported QOL outcomes in both the short- and long-term compared with SLNB alone. IFN therapy is associated with worse QOL outcomes compared with SLNB and CLND, an effect that may be sustained following cessation of adjuvant IFN.

Bone biology-related gingival transcriptome in ageing and periodontitis in non-human primates.

AIM: Cellular and molecular immunoinflammatory changes in gingival tissues drive alveolar bone loss in periodontitis. Since ageing is a risk factor for periodontitis, we sought to identify age-related gingival transcriptome changes associated with bone metabolism in both healthy and in naturally occurring periodontitis. MATERIALS AND METHODS: Adult (12-16 years) and aged (18-23 years) non-human primates (M. mulatta) (n = 24) were grouped into healthy and periodontitis. Gingival tissue samples were obtained and subjected to microarray analysis using the Gene Chip Macaque Genome Array. Gene expression profiles involved in osteoclast/osteoblast proliferation, adhesion and function were evaluated and compared across and between the age groups. QPCR was also performed on selected genes to validate microarray data. RESULTS: Healthy aged tissues showed a gene profile expression that suggest enhancement of osteoclastic adhesion, proliferation/survival and function (SPP1, TLR4, MMP8 and TFEC) and impaired osteoblastic activity (SMEK3P and SMAD5). The gingival transcriptome in both adult and aged animals with naturally occurring periodontitis (FOS, IL6, TLR4, MMP9, MMP10 and SPP1 genes) was consistent with a local inflammatory response driving towards bone/connective tissue destruction. CONCLUSION: A pro-osteoclastogenic gingival transcriptome is associated with periodontitis irrespective of age; however; a greater bone-destructive molecular environment is associated with ageing in healthy tissues.