Clinically Relevant Characterization of Lung Adenocarcinoma Subtypes Based on Cellular Pathways: An International Validation Study

Lung adenocarcinoma (AD) represents a predominant type of lung cancer demonstrating significant morphologic and molecular heterogeneity. We sought to understand this heterogeneity by utilizing gene expression analyses of 432 AD samples and examining associations between 27 known cancer-related pathways and the AD subtype, clinical characteristics and patient survival. Unsupervised clustering of AD and gene expression enrichment analysis reveals that cell proliferation is the most important pathway separating tumors into subgroups. Further, AD with increased cell proliferation demonstrate significantly poorer outcome and an increased solid AD subtype component. Additionally, we find that tumors with any solid component have decreased survival as compared to tumors without a solid component. These results lead to the potential to use a relatively simple pathological examination of a tumor in order to determine its aggressiveness and the patient's prognosis. Additional results suggest the ability to use a similar approach to determine a patient's sensitivity to targeted treatment. We then demonstrated the consistency of these findings using two independent AD cohorts from Asia (N = 87) and Europe (N = 89) using the identical analytic procedures

Drinking behaviour and alcohol-related harm amongst older adults: analysis of existing UK datasets.

Older adults experience age-related physiological changes that increase sensitivity and decrease tolerance to alcohol and there are a number of age-related harms such as falls, social isolation and elder abuse, which are compounded by alcohol misuse. Despite this unique vulnerability and the fact that the number of older adults is increasing, the literature on drinking behaviour and alcohol-related harm in older adults is sparse. This article describes a secondary analysis of UK data to address this knowledge gap

Downregulation of miR-99a/let-7c/miR-125b miRNA cluster predicts clinical outcome in patients with unresected malignant pleural mesothelioma

Malignant pleural mesothelioma (MPM) is an aggressive tumor with a dismal overall survival (OS) and to date no molecular markers are available to guide patient management. This study aimed to identify a prognostic miRNA signature in MPM patients who did not undergo tumor resection. Whole miRNA profiling using a microarray platform was performed using biopsies on 27 unresected MPM patients with distinct clinical outcome: 15 patients had short survival (OS < 12 months) and 12 patients had long survival (OS > 36 months). Three prognostic miRNAs (mir- 99a, let-7c, and miR-125b) encoded at the same cluster (21q21) were selected for further validation and tested on publicly available miRNA sequencing data from 72 MPM patients with survival data. A risk model was built based on these 3 miRNAs that was validated by quantitative PCR in an independent set of 30 MPM patients. High-risk patients had shorter median OS (7.6 months) as compared with low-risk patients (median not reached). In the multivariate Cox model, a high-risk score was independently associated with shorter OS (HR=3.14; 95% CI, 1.18-8.34; P=0.022). Our study identified that the downregulation of the miR-99a/let-7/miR-125b miRNA cluster predicts poor outcome in unresected MPM

Injectable Poly-l-Lactic Acid: A Novel Sculpting Agent for the Treatment of Dermal Fat Atrophy After Severe Acne

Acne vulgaris affects up to 80% of people 11 to 30 years of age, and scarring can occur for up to 95% of these patients. Scarring may be pitted or hypertrophic in nature, although in most cases it is atrophic. Atrophic acne scarring follows dermal collagen and fat loss after moderate to severe acne infection. Injectable poly-L-acid (PLLA) is a biocompatible, biodegradable, synthetic polymer device that is hypothesized to enhance dermal volume via the endogenous production of fibroblasts and, subsequently, collagen. The gradual improvements in cutaneous volume observed after treatment with injectable PLLA have been noted to last up to 2 years. The case studies presented describe the use of injectable PLLA to correct dermal fat loss in macular atrophic acne scarring of the cheeks. Two female patients underwent three treatment sessions with injectable PLLA over a 12-week period. At each treatment session, the reconstituted product was injected into the deep dermis under the depressed portion of the scar. Both patients were extremely pleased with their results at, respectively, 1- and 4-year follow-up evaluations. Patients experienced minimal swelling and redness after injection and no product-related adverse events such as papule and/or nodule formation. The author believes these data suggest that injectable PLLA is a good treatment option for the correction of macular atropic scarring with thin dermis (off-label use), particularly compared with other injectable fillers currently used for this indication that have shorter durations of effect

Pathophysiological mechanisms for the respiratory syncytial virus-reactive airway disease link

There is substantial epidemiological evidence supporting the concept that respiratory syncytial virus (RSV) lower respiratory tract infection in infancy may be linked to the development of reactive airway disease (RAD) in childhood. However, much less is known concerning the mechanisms by which this self-limiting infection leads to airway dysfunction that persists long after the virus is cleared from the lungs. A better understanding of the RSV–RAD link may have important clinical implications, particularly because prevention of RSV lower respiratory tract infection may reduce the occurrence of RAD later in life. Among the mechanisms proposed to explain the chronic sequelae of RSV infection is the interaction between the subepithelial neural network of the airway mucosa and the cellular effectors of inflammatory and immune responses to the virus. The body of clinical literature linking RSV and RAD is reviewed herein, as are the cellular and molecular mechanisms of neuroimmune interactions and neural remodeling that may underlie this link, and the possibility that preventing the infection may result in a decreased incidence of its chronic sequelae

Low oxygen affects photophysiology and the level of expression of two-carbon metabolism genes in the seagrass <i>Zostera muelleri</i>

© 2017, Springer Science+Business Media B.V. Seagrasses are a diverse group of angiosperms that evolved to live in shallow coastal waters, an environment regularly subjected to changes in oxygen, carbon dioxide and irradiance. Zostera muelleri is the dominant species in south-eastern Australia, and is critical for healthy coastal ecosystems. Despite its ecological importance, little is known about the pathways of carbon fixation in Z. muelleri and their regulation in response to environmental changes. In this study, the response of Z. muelleri exposed to control and very low oxygen conditions was investigated by using (i) oxygen microsensors combined with a custom-made flow chamber to measure changes in photosynthesis and respiration, and (ii) reverse transcription quantitative real-time PCR to measure changes in expression levels of key genes involved in C4 metabolism. We found that very low levels of oxygen (i) altered the photophysiology of Z. muelleri, a characteristic of C3 mechanism of carbon assimilation, and (ii) decreased the expression levels of phosphoenolpyruvate carboxylase and carbonic anhydrase. These molecular-physiological results suggest that regulation of the photophysiology of Z. muelleri might involve a close integration between the C3 and C4, or other CO2 concentrating mechanisms metabolic pathways. Overall, this study highlights that the photophysiological response of Z. muelleri to changing oxygen in water is capable of rapid acclimation and the dynamic modulation of pathways should be considered when assessing seagrass primary production

Selecting normalization genes for small diagnostic microarrays

BACKGROUND: Normalization of gene expression microarrays carrying thousands of genes is based on assumptions that do not hold for diagnostic microarrays carrying only few genes. Thus, applying standard microarray normalization strategies to diagnostic microarrays causes new normalization problems. RESULTS: In this paper we point out the differences of normalizing large microarrays and small diagnostic microarrays. We suggest to include additional normalization genes on the small diagnostic microarrays and propose two strategies for selecting them from genomewide microarray studies. The first is a data driven univariate selection of normalization genes. The second is multivariate and based on finding a balanced diagnostic signature. Finally, we compare both methods to standard normalization protocols known from large microarrays. CONCLUSION: Not including additional genes for normalization on small microarrays leads to a loss of diagnostic information. Using house keeping genes from the literature for normalization fails to work for certain datasets. While a data driven selection of additional normalization genes works well, the best results were obtained using a balanced signature

Large meta-analysis of multiple cancers reveals a common, compact and highly prognostic hypoxia metagene

BACKGROUND: There is a need to develop robust and clinically applicable gene expression signatures. Hypoxia is a key factor promoting solid tumour progression and resistance to therapy; a hypoxia signature has the potential to be not only prognostic but also to predict benefit from particular interventions. METHODS: An approach for deriving signatures that combine knowledge of gene function and analysis of in vivo co-expression patterns was used to define a common hypoxia signature from three head and neck and five breast cancer studies. Previously validated hypoxia-regulated genes (seeds) were used to generate hypoxia co-expression cancer networks. RESULTS: A common hypoxia signature, or metagene, was derived by selecting genes that were consistently co-expressed with the hypoxia seeds in multiple cancers. This was highly enriched for hypoxia-regulated pathways, and prognostic in multivariate analyses. Genes with the highest connectivity were also the most prognostic, and a reduced metagene consisting of a small number of top-ranked genes, including VEGFA, SLC2A1 and PGAM1, outperformed both a larger signature and reported signatures in independent data sets of head and neck, breast and lung cancers. CONCLUSION: Combined knowledge of multiple genes' function from in vitro experiments together with meta-analysis of multiple cancers can deliver compact and robust signatures suitable for clinical application

Top scoring pairs for feature selection in machine learning and applications to cancer outcome prediction

&lt;b&gt;Background&lt;/b&gt; The widely used k top scoring pair (k-TSP) algorithm is a simple yet powerful parameter-free classifier. It owes its success in many cancer microarray datasets to an effective feature selection algorithm that is based on relative expression ordering of gene pairs. However, its general robustness does not extend to some difficult datasets, such as those involving cancer outcome prediction, which may be due to the relatively simple voting scheme used by the classifier. We believe that the performance can be enhanced by separating its effective feature selection component and combining it with a powerful classifier such as the support vector machine (SVM). More generally the top scoring pairs generated by the k-TSP ranking algorithm can be used as a dimensionally reduced subspace for other machine learning classifiers.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Results&lt;/b&gt; We developed an approach integrating the k-TSP ranking algorithm (TSP) with other machine learning methods, allowing combination of the computationally efficient, multivariate feature ranking of k-TSP with multivariate classifiers such as SVM. We evaluated this hybrid scheme (k-TSP+SVM) in a range of simulated datasets with known data structures. As compared with other feature selection methods, such as a univariate method similar to Fisher's discriminant criterion (Fisher), or a recursive feature elimination embedded in SVM (RFE), TSP is increasingly more effective than the other two methods as the informative genes become progressively more correlated, which is demonstrated both in terms of the classification performance and the ability to recover true informative genes. We also applied this hybrid scheme to four cancer prognosis datasets, in which k-TSP+SVM outperforms k-TSP classifier in all datasets, and achieves either comparable or superior performance to that using SVM alone. In concurrence with what is observed in simulation, TSP appears to be a better feature selector than Fisher and RFE in some of the cancer datasets.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Conclusions&lt;/b&gt; The k-TSP ranking algorithm can be used as a computationally efficient, multivariate filter method for feature selection in machine learning. SVM in combination with k-TSP ranking algorithm outperforms k-TSP and SVM alone in simulated datasets and in some cancer prognosis datasets. Simulation studies suggest that as a feature selector, it is better tuned to certain data characteristics, i.e. correlations among informative genes, which is potentially interesting as an alternative feature ranking method in pathway analysis

Expression profiling of laser-microdissected intrapulmonary arteries in hypoxia-induced pulmonary hypertension

BACKGROUND: Chronic hypoxia influences gene expression in the lung resulting in pulmonary hypertension and vascular remodelling. For specific investigation of the vascular compartment, laser-microdissection of intrapulmonary arteries was combined with array profiling. METHODS AND RESULTS: Analysis was performed on mice subjected to 1, 7 and 21 days of hypoxia (FiO(2 )= 0.1) using nylon filters (1176 spots). Changes in the expression of 29, 38, and 42 genes were observed at day 1, 7, and 21, respectively. Genes were grouped into 5 different classes based on their time course of response. Gene regulation obtained by array analysis was confirmed by real-time PCR. Additionally, the expression of the growth mediators PDGF-B, TGF-β, TSP-1, SRF, FGF-2, TIE-2 receptor, and VEGF-R1 were determined by real-time PCR. At day 1, transcription modulators and ion-related proteins were predominantly regulated. However, at day 7 and 21 differential expression of matrix producing and degrading genes was observed, indicating ongoing structural alterations. Among the 21 genes upregulated at day 1, 15 genes were identified carrying potential hypoxia response elements (HREs) for hypoxia-induced transcription factors. Three differentially expressed genes (S100A4, CD36 and FKBP1a) were examined by immunohistochemistry confirming the regulation on protein level. While FKBP1a was restricted to the vessel adventitia, S100A4 and CD36 were localised in the vascular tunica media. CONCLUSION: Laser-microdissection and array profiling has revealed several new genes involved in lung vascular remodelling in response to hypoxia. Immunohistochemistry confirmed regulation of three proteins and specified their localisation in vascular smooth muscle cells and fibroblasts indicating involvement of different cells types in the remodelling process. The approach allows deeper insight into hypoxic regulatory pathways specifically in the vascular compartment of this complex organ