I MicroRNAs (miRNAs) are an abundant class of small non-protein-coding RNAs that function as negative gene regulators. They regulate diverse biological processes, and bioinformatic data indicates that each miRNA can control hundreds of gene targets, underscoring the potential influence of miRNAs on almost every genetic pathway. Recent evidence has shown that miRNA mutations or mis-expression correlate with various human cancers and indicates that miRNAs can function as tumour suppressors and oncogenes. miRNAs have been shown to repress the expression of important cancer-related genes and might prove useful in the diagnosis and treatment of cancer.

Oncomirs : microRNAs with a role in cancer

MicroRNAs (miRNAs) are an abundant class of small non-protein-coding RNAs that function as negative gene regulators They regulate diverse biological processes, and bioinformatic data indicates that each miRNA can control hundreds of gene targets, underscoring the potential influence of miRNAs on almost every genetic pathway Recent evidence has shown that miRNA mutations or mis-expression correlate with various human cancers and indicates that miRNAs can function as tumour suppressors and oncogenes miRNAs have been shown to repress the expression of important cancer-related genes and might prove useful in the diagnosis and treatment of cancer

/pdf/oncomirs-micrornas-with-a-role-in-cancer-4ryo1mpf3s.pdf

Oncomirs — microRNAs with a role in cancer

The therapeutic properties of light have been known for thousands of years, but it was only in the last century that photodynamic therapy (PDT) was developed. At present, PDT is being tested in the clinic for use in oncology--to treat cancers of the head and neck, brain, lung, pancreas, intraperitoneal cavity, breast, prostate and skin. How does PDT work, and how can it be used to treat cancer and other diseases?

Photodynamic therapy for cancer

Tissue homeostasis is regulated by apoptosis, the cell-suicide programme that is executed by proteases called caspases. The Bcl2 family of intracellular proteins is the central regulator of caspase activation, and its opposing factions of anti- and pro-apoptotic members arbitrate the life-or-death decision. Apoptosis is often impaired in cancer and can limit conventional therapy. A better understanding of how the Bcl2 family controls caspase activation should result in new, more effective therapeutic approaches.

The Bcl2 family: regulators of the cellular life-or-death switch.

Beneath the complexity and idiopathy of every cancer lies a limited number of 'mission critical' events that have propelled the tumour cell and its progeny into uncontrolled expansion and invasion One of these is deregulated cell proliferation, which, together with the obligate compensatory suppression of apoptosis needed to support it, provides a minimal 'platform' necessary to support further neoplastic progression Adroit targeting of these critical events should have potent and specific therapeutic consequences

Proliferation, cell cycle and apoptosis in cancer

Non beta cell progenitors of beta cells in pregnant mice

Aims/hypothesis
Irreversible arterial damage due to early effects of hypo- or hyperglycaemia could account for the limited success of glucose-lowering treatments in preventing cardiovascular disease (CVD) events. We hypothesised that even brief hypo- or hyperglycaemia could adversely affect arterial gene expression and that these changes, moreover, might not be fully reversible.

https://link.springer.com/content/pdf/10.1007%2Fs00125-010-1887-5.pdf

Short-term hyperglycaemia causes non-reversible changes in arterial gene expression in a fully 'switchable' in vivo mouse model of diabetes.

Background
The key factors which support re-expansion of beta cell numbers after injury are largely unknown. Insulin-like growth factor II (IGF-II) plays a critical role in supporting cell division and differentiation during ontogeny but its role in the adult is not known. In this study we investigated the effect of IGF-II on beta cell regeneration.

Methodology/Principal Findings
We employed an in vivo model of ‘switchable’ c-Myc-induced beta cell ablation, pIns-c-MycERTAM, in which 90% of beta cells are lost following 11 days of c-Myc (Myc) activation in vivo. Importantly, such ablation is normally followed by beta cell regeneration once Myc is deactivated, enabling functional studies of beta cell regeneration in vivo. IGF-II was shown to be re-expressed in the adult pancreas of pIns-c-MycERTAM/IGF-II+/+ (MIG) mice, following beta cell injury. As expected in the presence of IGF-II beta cell mass and numbers recover rapidly after ablation. In contrast, in pIns-c-MycERTAM/IGF-II+/− (MIGKO) mice, which express no IGF-II, recovery of beta cell mass and numbers were delayed and impaired. Despite failure of beta cell number increase, MIGKO mice recovered from hyperglycaemia, although this was delayed.

Conclusions/Significance
Our results demonstrate that beta cell regeneration in adult mice depends on re-expression of IGF-II, and supports the utility of using such ablation-recovery models for identifying other potential factors critical for underpinning successful beta cell regeneration in vivo. The potential therapeutic benefits of manipulating the IGF-II signaling systems merit further exploration.

/pdf/re-expression-of-igf-ii-is-important-for-beta-cell-4wmcaq0vix.pdf

Re-expression of IGF-II is important for beta cell regeneration in adult mice.

• Hereditary factors may, however, exert weak and subtle infl uences on the risk of development and subsequently the behavior of most if not all so called “ sporadic tumors, ” through a complex interplay between multiple, largely unknown polymorphic alleles, some of which may only be disadvantageous if the individual is exposed to particular environmental carcinogenic factors, such as tobacco smoke.

1 Overview of Cancer Biology

In the last years, bioimaging has turned from qualitative measurements towards a high-throughput and highcontent
modality, providing multiple variables for each biological sample analyzed. We present a system which
combines machine learning based semantic image annotation and visual data mining to analyze such new multivariate
bioimage data. Machine learning is employed for automatic semantic annotation of regions of interest.
The annotation is the prerequisite for a biological object-oriented exploration of the feature space derived from
the image variables. With the aid of visual data mining, the obtained data can be explored simultaneously in
the image as well as in the feature domain. Especially when little is known of the underlying data, for example
in the case of exploring the effects of a drug treatment, visual data mining can greatly aid the process of
data evaluation. We demonstrate how our system is used for image evaluation to obtain information relevant
to diabetes study and screening of new anti-diabetes treatments. Cells of the Islet of Langerhans and whole
pancreas in pancreas tissue samples are annotated and object specific molecular features are extracted from
aligned multichannel fluorescence images. These are interactively evaluated for cell type classification in order
to determine the cell number and mass. Only few parameters need to be specified which makes it usable also for
non computer experts and allows for high-throughput analysis.

Stella Pelengaris

Papers

Non beta cell progenitors of beta cells in pregnant mice

Short-term hyperglycaemia causes non-reversible changes in arterial gene expression in a fully 'switchable' in vivo mouse model of diabetes.

Re-expression of IGF-II is important for beta cell regeneration in adult mice.

1 Overview of Cancer Biology

A way toward analyzing high-content bioimage data by means of semantic annotation and visual data mining