FOXM1 coming of age: time for translation into clinical benefits?

A decade since the first evidence implicating the cell cycle transcription factor Forkhead Box M1 (FOXM1) in human tumorigenesis, a slew of subsequent studies revealed an oncogenic role of FOXM1 in the majority of human cancers including oral, nasopharynx, oropharynx, esophagus, breast, ovary, prostate, lung, liver, pancreas, kidney, colon, brain, cervix, thyroid, bladder, uterus, testis, stomach, skin, and blood. Its aberrant upregulation in almost all different cancer types suggests a fundamental role for FOXM1 in tumorigenesis. Its dose-dependent expression pattern correlated well with tumor progression starting from cancer predisposition and initiation, early premalignancy and progression, to metastatic invasion. In addition, emerging studies have demonstrated a causal link between FOXM1 and chemotherapeutic drug resistance. Despite the well-established multifaceted roles for FOXM1 in all stages of oncogenesis, its translation into clinical benefit is yet to materialize. In this contribution, I reviewed and discussed how our current knowledge on the oncogenic mechanisms of FOXM1 could be exploited for clinical use as biomarker for risk prediction, early cancer screening, molecular diagnostics/prognostics, and/or companion diagnostics for personalized cancer therapy

A nonparametric HMM for genetic imputation and coalescent inference

Genetic sequence data are well described by hidden Markov models (HMMs) in which latent states correspond to clusters of similar mutation patterns. Theory from statistical genetics suggests that these HMMs are nonhomogeneous (their transition probabilities vary along the chromosome) and have large support for self transitions. We develop a new nonparametric model of genetic sequence data, based on the hierarchical Dirichlet process, which supports these self transitions and nonhomogeneity. Our model provides a parameterization of the genetic process that is more parsimonious than other more general nonparametric models which have previously been applied to population genetics. We provide truncation-free MCMC inference for our model using a new auxiliary sampling scheme for Bayesian nonparametric HMMs. In a series of experiments on male X chromosome data from the Thousand Genomes Project and also on data simulated from a population bottleneck we show the benefits of our model over the popular finite model fastPHASE, which can itself be seen as a parametric truncation of our model. We find that the number of HMM states found by our model is correlated with the time to the most recent common ancestor in population bottlenecks. This work demonstrates the flexibility of Bayesian nonparametrics applied to large and complex genetic data

Bypassing the flush, creating new resources: analysing alternative sanitation futures in London

The flush toilet is an illogical form of sanitation from the point of view of water conservation, nutrient recovery and water pollution. Places such as London, with one of the oldest flushing toilet and sewer systems in the world, bears witness to the limits of its universal applicability through dwindling freshwater resources and polluted waterways. It is therefore important to develop new forms of sanitation infrastructure. An actor–network theory coevolution framework is used to explore and gain insights into the coevolution pathways for new types and paradigms of sanitation in London, where waterborne sanitation is currently prevalent. This approach shows that while flushing toilets are currently stable network configurations, there are coevolution pathways that would shift the system towards dry sanitation. The quantity of freshwater resources available for toilet flushing was the main actant cited for the development of these coevolution pathways

Coevolving water sustainability in London

London’s water infrastructure has been developed over many centuries. It is a system of centralised water distribution and drainage that has formed the model for water infrastructure systems in cities around the world. However, this system is unsustainable: its incapacity to respond to the growth of populations and increasing water consumption per capita has led to the degradation of aquatic environments. A fresh approach is needed in order to identify urban water cycle solutions that can address these problems. This paper outlines an amalgamated theoretical framework – coevolutionary actor–network theory – and its use by the author to develop a methodology capable of formulating how London’s urban water cycle might coevolve towards sustainability in the future. This framework allows the tracing of relationships between human and nonhuman influences and environments that coalesce into large infrastructural systems. Two coevolutionary possibilities towards water sustainability were identified. One lay in diversifying types of water reuse; the other in multifarious forms of waste harvesting. The paper further contends that this theoretical approach and set of methods could also be applied to other infrastructure systems such as energy, waste, and air pollution

Inconsistency of Pitman-Yor process mixtures for the number of components

In many applications, a finite mixture is a natural model, but it can be difficult to choose an appropriate number of components. To circumvent this choice, investigators are increasingly turning to Dirichlet process mixtures (DPMs), and Pitman-Yor process mixtures (PYMs), more generally. While these models may be well-suited for Bayesian density estimation, many investigators are using them for inferences about the number of components, by considering the posterior on the number of components represented in the observed data. We show that this posterior is not consistent --- that is, on data from a finite mixture, it does not concentrate at the true number of components. This result applies to a large class of nonparametric mixtures, including DPMs and PYMs, over a wide variety of families of component distributions, including essentially all discrete families, as well as continuous exponential families satisfying mild regularity conditions (such as multivariate Gaussians).Comment: This is a general treatment of the problem discussed in our related article, "A simple example of Dirichlet process mixture inconsistency for the number of components", Miller and Harrison (2013) arXiv:1301.270

Identification of multidrug chemoresistant genes in head and neck squamous cell carcinoma cells

Multidrug resistance renders treatment failure in a large proportion of head and neck squamous cell carcinoma (HNSCC) patients that require multimodal therapy involving chemotherapy in conjunction with surgery and/or radiotherapy. Molecular events conferring chemoresistance remain unclear. Through transcriptome datamining, 28 genes were subjected to pharmacological and siRNA rescue functional assays on 12 strains of chemoresistant cell lines each against cisplatin, 5-fluorouracil (5FU), paclitaxel (PTX) and docetaxel (DTX). Ten multidrug chemoresistance genes (TOP2A, DNMT1, INHBA, CXCL8, NEK2, FOXO6, VIM, FOXM1B, NR3C1 and BIRC5) were identified. Of these, four genes (TOP2A, DNMT1, INHBA and NEK2) were upregulated in an HNSCC patient cohort (n = 221). Silencing NEK2 abrogated chemoresistance in all drug-resistant cell strains. INHBA and TOP2A were found to confer chemoresistance in majority of the drug-resistant cell strains whereas DNMT1 showed heterogeneous results. Pan-cancer Kaplan-Meier survival analysis on 21 human cancer types revealed significant prognostic values for INHBA and NEK2 in at least 16 cancer types. Drug library screens identified two compounds (Sirodesmin A and Carfilzomib) targeting both INHBA and NEK2 and re-sensitised cisplatin-resistant cells. We have provided the first evidence for NEK2 and INHBA in conferring chemoresistance in HNSCC cells and siRNA gene silencing of either gene abrogated multidrug chemoresistance. The two existing compounds could be repurposed to counteract cisplatin chemoresistance in HNSCC. This finding may lead to novel personalised biomarker-linked therapeutics that can prevent and/or abrogate chemoresistance in HNSCC and other tumour types with elevated NEK2 and INHBA expression. Further investigation is necessary to delineate their signalling mechanisms in tumour chemoresistance

Transcending Illness: Post-Traumatic Growth in Leukemia and Lymphoma Survivors.

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2018

Dependence of Adhesion Property of Epoxidized Natural Rubber (ENR 25)/Ethylene-Propylene-Diene Rubber Blend Adhesives Crosslinked by Benzoyl Peroxide

The loop tack, peel strength, and shear strength of crosslinked epoxidized natural rubber (ENR 25)/ethylene-propylene-diene rubber (EPDM) blend adhesives were investigated. Coumarone-indene resin, toluene, and benzoyl peroxide were used as the tackifier, solvent, and crosslinking agent, respectively, throughout the experiment. The adhesive was coated on a polyethylene terephthalate (PET) substrate using a SHEEN hand coater at 6