Hidden Markov models for cancer classification using gene expression profiles

This paper introduces an approach to cancer classification through gene expression profiles by designing supervised learning hidden Markov models (HMMs). Gene expression of each tumor type is modelled by an HMM, which maximizes the likelihood of the data. Prominent discriminant genes are selected by a novel method based on a modification of the analytic hierarchy process (AHP). Unlike conventional AHP, the modified AHP allows to process quantitative factors that are ranking outcomes of individual gene selection methods including t-test, entropy, receiver operating characteristic curve, Wilcoxon test and signal to noise ratio. The modified AHP aggregates ranking results of individual gene selection methods to form stable and robust gene subsets. Experimental results demonstrate the performance dominance of the HMM approach against six comparable classifiers. Results also show that gene subsets generated by modified AHP lead to greater accuracy and stability compared to competing gene selection methods, i.e. information gain, symmetrical uncertainty, Bhattacharyya distance, and ReliefF. The modified AHP improves the classification performance not only of the HMM but also of all other classifiers. Accordingly, the proposed combination between the modified AHP and HMM is a powerful tool for cancer classification and useful as a real clinical decision support system for medical practitioners.

Cancer: an emergent property of disturbed resource-rich environments? Ecology meets personalized medicine

For an increasing number of biologists, cancer is viewed as a dynamic system governed by evolutionary and ecological principles. Throughout most of human history, cancer was an uncommon cause of death and it is generally accepted that common components of modern culture, including increased physiological stresses and caloric intake, favor cancer development. However, the precise mechanisms for this linkage are not well understood. Here, we examine the roles of ecological and physiological disturbances and resource availability on the emergence of cancer in multicellular organisms. We argue that proliferation of 'profiteering phenotypes' is often an emergent property of disturbed, resource-rich environments at all scales of biological organization. We review the evidence for this phenomenon, explore it within the context of malignancy, and discuss how this ecological framework may offer a theoretical background for novel strategies of cancer prevention. This work provides a compelling argument that the traditional separation between medicine and evolutionary ecology remains a fundamental limitation that needs to be overcome if complex processes, such as oncogenesis, are to be completely understood.

Development of a measure of health literacy for caregivers of people with cancer

Caregivers play a key role in supporting people with cancer. Little is known about challenges that caregivers might have when finding and understanding health information, making health-related decisions, and navigating the healthcare system. Using an innovative mixed-methods approach, the study developed and evaluated a tool to measure cancer caregiver health literacy.

Animal behaviour and cancer

Scientists are increasingly coming to realize that oncogenic phenomena are both frequent and detrimental for animals, and must therefore be taken into account when studying the biology of wildlife species and ecosystem functioning. Here, we argue that several behaviours that are routine in an individual's life can be associated with cancer risks, or conversely prevent/cure malignancies and/or alleviate their detrimental consequences for fitness. Although such behaviours are theoretically expected to be targets for natural selection, little attention has been devoted to explore how they influence animal behaviour. This essay provides a summary of these issues as well as an overview of the possibilities offered by this research topic, including possible applications for cancer prevention and treatments in humans.

EpCAM aptamer-mediated survivin silencing sensitized cancer stem cells to doxorubicin in a breast cancer model

Understanding the molecular basis of drug resistance and utilising this information to overcome chemoresistance remains a key challenge in oncology. Here we report that survivin, a key protein implicated in drug resistance, is overexpressed in cancer stem cell pool of doxorubicin-resistant breast cancer cells. Moreover, by utilising an active targeting system consisting of an RNA aptamer targeted against the epithelial cell adhesion molecule and a Dicer substrate survivin siRNA, we could deliver a high dose of the siRNA to cancer stem cells in xenograft tumours. Importantly, silencing of survivin with this aptamer-siRNA chimera in cancer stem cell population led to the reversal of chemoresistance, such that combined treatment with low dose of doxorubicin inhibited stemness, eliminated cancer stem cells via apoptosis, suppressed tumour growth, and prolonged survival in mice bearing chemoresistant tumours. This strategy for in vivo cancer stem cell targeting has wide application for future effective silencing of anti-death genes and in fact any dysregulated genes involved in chemoresistance and tumour relapse.

Manufacturing techniques and surface engineering of polymer based nanoparticles for targeted drug delivery to cancer

The evolution of polymer based nanoparticles as a drug delivery carrier via pharmaceutical nano/microencapsulation has greatly promoted the development of nano- and micro-medicine in the past few decades. Poly(lactide-co-glycolide) (PLGA) and chitosan, which are biodegradable and biocompatible polymers, have been approved by both the Food & Drug Administration (FDA) and European Medicine Agency (EMA), making them ideal biomaterials that can be advanced from laboratory development to clinical oral and parental administrations. PLGA and chitosan encapsulated nanoparticles (NPs) have successfully been developed as new oral drug delivery systems with demonstrated high efficacy. This review aims to provide a comprehensive overview of the fabrication of PLGA and chitosan particulate systems using nano/microencapsulation methods, the current progress and the future outlooks of the nanoparticulate drug delivery systems. Especially, we focus on the formulations and nano/micro-encapsulation techniques using top-down techniques. It also addresses how the different phases including the organic and aqueous ones in the emulsion system interact with each other and subsequently influence the properties of the drug delivery system. Besides, surface modification strategies which can effectively engineer intrinsic physicochemical properties are summarised. Finally, future perspectives and potential directions of PLGA and chitosan nano/microencapsulated drug systems are outlined.

Modified AHP for gene selection and cancer classification using type-2 fuzzy logic

This paper proposes a modification to the analytic hierarchy process (AHP) to select the most informative genes that serve as inputs to an interval type-2 fuzzy logic system (IT2FLS) for cancer classification. Unlike the conventional AHP, the modified AHP allows us to process quantitative factors that are ranking outcomes of individual gene selection methods including t-test, entropy, receiver operating characteristic curve, Wilcoxon test, and signal-to-noise ratio. The IT2FLS is introduced for the classification task due to its great ability for handling nonlinear, noisy, and outlier data, which are common problems in cancer microarray gene expression profiles. An unsupervised learning strategy using the fuzzy c-means clustering is employed to initialize parameters of the IT2FLS. Other classifiers such as multilayer perceptron network, support vector machine, and fuzzy ARTMAP are also implemented for comparisons. Experiments are carried out on three well-known microarray datasets: diffuse large B-cell lymphoma, leukemia cancer, and prostate. Rather than the traditional cross validation, leave-one-out cross-validation strategy is applied for the experiments. Results demonstrate the performance dominance of the IT2FLS against the competing classifiers. More noticeably, the modified AHP improves the classification performance not only of the IT2FLS but of all other classifiers as well. Accordingly, the proposed combination between the modified AHP and IT2FLS is a powerful tool for cancer classification and can be implemented as a real clinical decision support system that is useful for medical practitioners.

Delivery of fluorouracil and siRNA by mesoporous silica nanoparticles to drug resistant colorectal cancer

 Mesoporous silica nanoparticle based drug and gene delivery system was developed to overcome the acquired drug resistance in colorectal cancer by targeted delivery of anti-cancer drug in the cytoplasm of the cancer cells and silencing the gene expression related to drug resistance.

Hypertension, antihypertensive treatment and cancer incidence and mortality : a pooled collaborative analysis of 12 Australian and New Zealand cohorts

BACKGROUND: Observational studies examining associations between hypertension and cancer are inconsistent. We explored the association of hypertension, graded hypertension and antihypertensive treatment with cancer incidence and mortality. METHOD: Eighty-six thousand five hundred and ninety-three participants from the Australian and New Zealand Diabetes and Cancer Collaboration were linked to the National Death Index and Australian Cancer Database. Cox proportional hazards models estimated hazard ratios and 95% confidence intervals (95% CI) for the association of treated and untreated hypertension with cancer incidence and mortality. RESULTS: Over a median follow-up of 15.1 years, 12 070 incident and 4350 fatal cancers were identified. Untreated and treated hypertension, compared with normotension, were associated with an increased risk for cancer incidence [hazard ratio 1.06, 95% CI (1.00-1.11) and 1.09 (1.02-1.16) respectively], and cancer mortality (1.07, 0.98-1.18) and (1.15, 1.03-1.28), respectively. When compared with untreated hypertension, treated hypertension did not have a significantly greater risk for cancer incidence (1.03, 0.97-1.10) or mortality (1.07, 0.97-1.19). A significant dose-response relationship was observed between graded hypertension and cancer incidence and mortality; Ptrend = 0.053 and Ptrend = 0.001, respectively. When stratified by treatment status, these relationships remained significant in untreated, but not in treated, hypertension. CONCLUSION: Hypertension, both treated and untreated, is associated with a modest increased risk for cancer incidence and mortality. Similar risks in treated and untreated hypertension suggest that the increased cancer risk is not explained by the use of antihypertensive treatment.