Bayesian data integration and variable selection for pan-cancer survival prediction using protein expression data

Accurate prognostic prediction using molecular information is a challenging area of research, which is essential to develop precision medicine. In this paper, we develop translational models to identify major actionable proteins that are associated with clinical outcomes, like the survival time of patients. There are considerable statistical and computational challenges due to the large dimension of the problems. Furthermore, data are available for different tumor types; hence data integration for various tumors is desirable. Having censored survival outcomes escalates one more level of complexity in the inferential procedure. We develop Bayesian hierarchical survival models, which accommodate all the challenges mentioned here. We use the hierarchical Bayesian accelerated failure time model for survival regression. Furthermore, we assume sparse horseshoe prior distribution for the regression coefficients to identify the major proteomic drivers. We borrow strength across tumor groups by introducing a correlation structure among the prior distributions. The proposed methods have been used to analyze data from the recently curated “The Cancer Proteome Atlas” (TCPA), which contains reverse-phase protein arrays–based high-quality protein expression data as well as detailed clinical annotation, including survival times. Our simulation and the TCPA data analysis illustrate the efficacy of the proposed integrative model, which links different tumors with the correlated prior structures.     

Reduction of nuclear Y654-p-β-catenin expression through SH3GL2-meditated downregulation of EGFR in chemotolerance TNBC: Clinical and prognostic importance

Triple negative breast cancer (TNBC) originates from a less differentiated ductal cell of breast, which is less sensitive to chemotherapy. The chemotolerance mechanism of TNBC has not yet been studied in detail. For this reason, molecular profiles (expression/genetic/epigenetic) of Y654-p-β-catenin (active) and its kinase epidermal growth factor receptor (EGFR) along with SH3GL2 (regulator of EGFR homeostasis) were compared between neoadjuvant chemotherapy treated (NACT) and pretherapeutic TNBC samples. Reduced nuclear expression of Y654-p-β-catenin protein with low proliferation index and CD44 prevalence showed concordance with reduced expression of EGFR/Y1045-p-EGFR proteins in the NACT samples than the pretherapeutic TNBC samples. Infrequent messenger RNA expression, gene amplification (10–32.5%), and mutation (1%) of EGFR were seen in the TNBC samples irrespective of therapy, suggesting the importance of EGFR protein stabilization in this tumor. The upregulation of SH3GL2 seen in the NACT samples in contrast to the pretherapeutic samples might be due to its promoter hypomethylation, as seen in the quantitative methylation assay. A similar trend of upregulation of SH3GL2 and downregulation of EGFR, Y1045-p-EGFR, Y654-p-β-catenin were seen in the MDA-MB-231 cell line using antharacycline antitumor drugs (doxorubicin/nogalamycin). The NACT patients with reduced expression of Y654-p-β-catenin and/or EGFR and high expression of SH3GL2 showed comparatively better prognosis than the pretherapeutic patients. Thus, our study showed that reduced nuclear expression of Y654-p-β-catenin in NACT samples due to downregulation of EGFR protein through promoter hypomethylation-mediated upregulation of SH3GL2, resulting in low proliferation index/CD44 prevalence with better prognosis of the NACT patients, might have an important role in the chemotolerance of TNBC.     

Effect of nitric oxide signaling in bacterial-treated soybean plant under salt stress

To understand protective roles of nitric oxide against salt stress, the effects of exogenous sodium nitroprusside on activities of lipoxygenase, peroxidase, phenylalanine ammonialyase, catalase, superoxide dismutase enzymes, proline accumulation, and distribution of sodium in soybean plants under salt were determined. Application of sodium nitroprusside + bacterium enhanced plant growth-promotion characteristics, activities of different enzymes, and proline accumulation in the presence of sodium nitroprusside under salt stress. Treatment with NaCl at 200 mM and sodium nitroprusside (0.1 mM) reduced Na⁺ levels but increased K⁺ levels in leaves in comparison with the NaCl-treated plants. Correspondingly, the plants treated with exogenous sodium nitroprusside and NaCl maintained a lower ratio of [Na⁺]/[K⁺] in NaCl-stressed plants.     

In silico investigation of novel biological pathways: The role of CD200 in regulation of T cell priming in experimental autoimmune encephalomyelitis

The use of simulation to investigate biological domains will inevitably lead to the need to extend existing simulations as new areas of these domains become more fully understood. Such simulation extensions can entail the incorporation of additional cell types, molecules or molecular pathways, all of which can exert a profound influence on the simulation behaviour. Where the biological domain is not well characterised, a structured development methodology must be employed to ensure that the extended simulation is well aligned with its predecessor. We develop and discuss such a methodology, relying on iterative simulation development and sensitivity analysis. The utility of this methodology is demonstrated using a case study simulation of experimental autoimmune encephalomyelitis (EAE), a murine T cell-mediated autoimmune disease model of multiple sclerosis, where it is used to investigate the activity of an additional regulatory pathway. We discuss how application of this methodology guards against creating inappropriate simulation representations of the biology when investigating poorly characterised biological mechanisms.     

Meander: visually exploring the structural variome using space-filling curves

The introduction of next generation sequencing methods in genome studies has made it possible to shift research from a gene-centric approach to a genome wide view. Although methods and tools to detect single nucleotide polymorphisms are becoming more mature, methods to identify and visualize structural variation (SV) are still in their infancy. Most genome browsers can only compare a given sequence to a reference genome; therefore, direct comparison of multiple individuals still remains a challenge. Therefore, the implementation of efficient approaches to explore and visualize SVs and directly compare two or more individuals is desirable. In this article, we present a visualization approach that uses space-filling Hilbert curves to explore SVs based on both read-depth and pair-end information. An interactive open-source Java application, called Meander, implements the proposed methodology, and its functionality is demonstrated using two cases. With Meander, users can explore variations at different levels of resolution and simultaneously compare up to four different individuals against a common reference. The application was developed using Java version 1.6 and Processing.org and can be run on any platform. It can be found at http://homes.esat.kuleuven.be/~bioiuser/meander.     

Binding of the plant alkaloid aristololactam-β-d-glucoside and antitumor antibiotic daunomycin to single stranded polyribonucleotides

Background

Interaction of the plant alkaloid aristololactam-β-d-glucoside and the antitumor drug daunomycin with single stranded RNAs poly(G), poly(I), poly(C) and poly(U) has been investigated.

Methods

Biophysical techniques of absorption, fluorescence, competition dialysis, circular dichroism, and microcalorimetry have been used.

Results

Absorption and fluorescence studies have revealed noncooperative binding of ADG and DAN to the single stranded RNAs. The binding affinity of ADG varied as poly(G) > poly(I) > > poly(C) > poly(U). The affinity of DAN was one order higher than that of ADG and varied as poly(G) > poly(I) > poly(U) > poly(C). This binding preference was further confirmed by competition dialysis assay. The thermodynamics of the binding was characterised to be favourable entropy and enthalpic terms but their contributions were different for different systems. The major non-polyelectrolytic contribution to the binding revealed from salt dependent data appears to be arising mostly from stacking of DAN and ADG molecules with the bases leading to partial intercalation to single stranded RNA structures. Small negative heat capacity values have been observed in all the four cases.

Conclusions

This study presents the comparative structural and thermodynamic profiles of the binding of aristololactam-β-d-glucoside and daunomycin to single stranded polyribonucleotides.

General significance

These results suggest strong, specific but differential binding of these drug molecules to the single stranded RNAs and highlight the role of their structural differences in the interaction profile.     

Screening of banana bunchy top virus through multiplex PCR approach

Bunchy top disease caused by the banana bunchy top virus (BBTV) is a serious disease in hill banana. Detection of the BBTV infection in the planting material could help in the effective management of the disease. An attempt was made to develop a sensitive polymerase chain reaction (PCR) and multiplex PCR-based method for detection of BBTV in hill banana. DNA was isolated from the experimental plants at third and sixth months after planting. Multiplex PCR was done with Coat Protein (CP) and Replicase (Rep) gene-specific primer, and banana ethylene insensitive like protein (EISL) primer as internal control to identify failure in PCR reaction. This study revealed that multiplex PCR is effective for BBTV screening in hill banana with the advantage of overcoming the false positive in PCR amplification.     

Genetic and physiological relatedness of antagonistic Trichoderma isolates against soil borne plant pathogenic fungi

In this study, the in vitro potential of 42 Trichoderma spp. were evaluated against four isolates of soil borne phytopathogenic fungi viz., Rhizoctonia solani, Macrophomina sp., Sclerotium rolfsii and Pythium aphanidermatum in dual culture techniques and through production of volatile and non-volatile inhibitors. In vitro screening results showed that the proportion of isolates with antagonistic activities was highest for the S. rolfsii followed by R. solani, Macrophomina sp. and P. aphanidermatum, respectively. The isolates TNT1, TNP2 and TWP1 showed consistent results in volatile and non-volatile activity in vitro against any of the two pathogens tested. Based on genomic finger prints, potential isolates showed no particular correlation between the origin of the isolates and the Random Amplified Polymorphic DNA (RAPD) groups could not be established. However, the polymorphism shown by the isolates did not correlate to their level of antagonism. Whereas, in physiology studies using BIOLOG (microbial identification system), three groups were formed, one group consists with 14 different Trichoderma species and two groups with two isolates each comprised of only T. koningii and T. viride.     

Epidemiology and prediction of brown leaf rust of mulberry caused by Peridiopsora mori

Brown leaf rust (BLR) caused by Peridiopsora mori is one of the major foliar diseases of mulberry (Morus sp.) in the subtropical hills of eastern India. The disease appeared in first week of August and continued up to September with maximum severity in second and third week of September. The disease symptoms appeared at atmospheric temperature (27.00–20.07°C), relative humidity (92.14–82.43%), rainfall (11.20 cm) and rainy days (7) of the preceding week. Disease severity (>50 PDI) was observed at temperature (26.29–19.29°C), relative humidity (94.14–80.14%), rainfall (4.12 cm) and number of rainy days (2–3 days). Apparent rate of infection was found high at temperature (27.00–19.83°C), relative humidity (94.67–85.00%), rainfall (4.6 cm) and rainy days (2) of the preceding week. The correlation coefficient between disease severity and average meteorological factors of the preceding 7 days revealed that BLR disease severity showed significant negative correlation with minimum temperature. It was also revealed that contribution of maximum and minimum temperature 42.23% and 35.21%, maximum and minimum relative humidity (RH) 11.23% and 10.69% and rainfall and number of rainy days 0.11% and 0.50%, respectively towards development of BLR disease severity. Multiple regression analysis revealed that average of maximum and minimum temperatures and minimum RH of preceding 7 days were found to maximally influence BLR disease severity.