A new study from researchers at the University of Ottawa Heart Institute (UOHI), sheds light on a mysterious gene that likely influences cardiovascular health. After five years, UOHI researchers now know how one genetic variant works and suspect that it contributes to the development of heart disease through processes that promote chronic inflammation and cell division.
Researchers at the Ruddy Canadian Cardiovascular Genetics Centre had initially identified a variant in a gene called SPG7 as a potential contributor to coronary artery disease several years ago, but its role in multiple health processes made it difficult to tease out how it affects heart disease.
The gene holds instructions for producing a protein called SPG7. This protein resides in mitochondria—the small power plants of cells that produce the energy cells need to function. SPG7’s role is to help break down and recycle other damaged proteins within the mitochondria.
Normally, SPG7 requires a partner protein to activate itself and start this breakdown process. But, in people who carry the genetic variant in question, SPG7 can activate itself in certain circumstances, leading to increased production of free radicals and more rapid cell division. These factors contribute to inflammation and atherosclerosis.
‘We think this variant would definitely heighten the state of inflammation, and we know that inflammation affects diabetes and heart disease,’ said Dr. Stewart, Principal Investigator in the Ruddy Canadian Cardiovascular Genetics Centre and senior author of the study. ‘Interestingly, the variant also makes people more resistant to the toxic side effects of some chemotherapy drugs.’
From an evolutionary perspective, this resistance could help such a genetic variant gain a stable place in the human genome. Between 13 and 15 per cent of people of European descent possess this variant.
‘The idea of mitochondria contributing to inflammation isn’t new,’ concluded Dr. Stewart. ‘But what is new is that we’ve found one of the switches that regulate this process. We’re excited, because once you know where the switches are, you can start looking for ways to turn them on and off.’ EurekAlert

A research team lead by Academy Professor Kari Rissanen at the University of Jyväskylä has discovered a new water-soluble fluorescent detection system that is extremely sensitive to pyrophosphate (PPi).
Pyrophosphate has a key role in energy transduction, DNA replication and other metabolic processes that are dysregulated in cancer cells. The discovery might lead to the development of a method for early detection of cancer cells.

The team developed a simple metal complex which shows an intense orange fluorescent colour in the presence of very low concentration of pyrophosphate (PPi) in water. The complex, also called a probe, had almost 1000 times higher level of response than earlier methods and an unprecedented sensitivity to detect PPi at a sub-nanomolar level. The discovery represents the first water-soluble fluorescent sensor that is capable of detecting pyrophosphate at this sensitivity level under physiological conditions.

The highly sensitive probes or sensors that are able to report the PPi level could lead to improved cancer diagnostics, since PPi plays a key role in energy transduction, DNA replication and other metabolic processes that are seriously misbehaving in cancer cells. All earlier PPi-selective sensor molecules or complexes have suffered from poor water solubility and low sensitivity in water. They can reach only micromolar levels and, thus, researchers have had to rely on protein-based probes that have their own limitations.

The researchers were able to show that the probe can image the pyrophosphate in the nuclei of living (HeLa) cells, making it an excellent probe for live cell pyrophosphahe imaging. The HeLa cells, originally from Henrietta Lack’s cervix carcinoma, are the most long-lived human cancer cell line and are often used as a cancer cell model. In addition to their applicability in water, they can easily be formulated into a hydrogel and coated onto paper strips for low-cost pyrophosphate detection. University of Jyväskylä

Case Western Reserve researchers have discovered that a protein previously implicated in disease plays such a positive role in learning and memory that it may someday contribute to cures of cognitive impairments. The findings regarding the potential virtues of fatty acid binding protein 5 (FABP5) — usually associated with cancer and psoriasis.

‘Overall, our data show that FABP5 enhances cognitive function and that FABP5 deficiency impairs learning and memory functions in the brain hippocampus region,’ said senior author Noa Noy, PhD, a professor of pharmacology at the School of Medicine. ‘We believe if we could find a way to upregulate the expression of FABP5 in the brain, we might have a therapeutic handle on cognitive dysfunction or memory impairment in some human diseases.’

FABP5 resides in many tissues and is especially highly expressed in the brain. Noy and her Case Western Reserve School of Medicine and National Institute on Alcohol Abuse and Alcoholism colleagues particularly wanted to understand how this protein functioned in neurons. They performed imaging studies comparing the activation of a key transcription factor in the brain tissue of normal mice and in FABP5-deficient mice. (Transcription factor is a protein the controls the flow of genetic information). The investigations revealed that FABP5 performs two different functions in neurons. First, it facilitates the degradation of endocannabinoids, which are neurological modulators controlling appetite, pain sensation, mood and memory. Second, FABP5 regulates gene expression, a process that essentially gives cells their marching orders on structure, appearance and function.

‘FABP5 improves learning and memory both because it delivers endocannabinoids to cellular machinery that breaks them down and because it shuttles compounds to a transcription factor that increases the expression of cognition-associated genes,’ Noy said.

Even though endocannabinoids affect essential physiological processes from appetite to memory, the ‘cannabinoid’ part of the word signifies that these natural biological compounds act similarly to drugs such as marijuana and hashish. Too much endocannabinoid can lead to impaired learning and memory.

In simple terms, FABP5 transports endocannabinoids for processing. FABP5 functions like a bus and carries the brain’s endocannabinoids and their biological products to two stations within the neuron cell. FABP5 captures endocannabinoids entering the neuron and delivers them to an enzyme that degrades them (station 1). Then, that degraded product is picked up by the same protein (FABP5) and shuttled to the cell nucleus — specifically, to a transcription factor within it (station 2). Binding of the degraded product activates the transcription factor and allows it to induce expression of multiple genes. The genes that are induced in this case tell the cells to take steps that promote learning and memory.

Noy and associates also compared memory and learning in FABP5-deficient mice and in normal ones. In one test, both sets of mice repeatedly swam in mazes that had a platform in one established location where they could climb out of the water. During subsequent swims, the wild-type mice reached the platform quickly because they had learned — and remembered — its location. Their FABP5-deficient counterparts took much longer, typically finding the platform’s location by chance.

‘In addition to regulating cell growth as in skin and in cancer cells, for example, FABP5 also plays a key role in neurons of the brain,’ Noy said. ‘FABP5 controls the biological actions of small compounds that affect memory and learning and that activate a transcription factor, which regulates neuronal function.’ Case Western Reserve University School of Medicine

During breast-tissue development, a transcription factor called SLUG plays a role in regulating stem cell function and determines whether breast cells will mature into luminal or basal cells.

Studying factors, such as SLUG, that regulate stem-cell activity and breast-cell identity are important for understanding how breast tumours arise and develop into different subtypes. Ultimately, this knowledge may help the development of novel therapies targeted to specific breast-tumour subtypes.

Background: Stem cells are immature cells that can differentiate, or develop, into different cell types. Stem cells are important for replenishing cells in many tissues throughout the body. Defects that affect stem-cell activity can lead to cancer because mutations in these cells can cause uncontrollable growth. Some transcription factors regulate the differentiation or ‘programming’ of breast stem cells into the more mature cells of the breast tissue. Abnormal expression of these transcription factors can change the normal programming of cells, which can lead to imbalances in cell types and the over-production of cells with enhanced properties of stem cells.

Breast tissue has two main types of cells: luminal cells and basal cells. Transcription factors, like SLUG, help control whether cells are programmed to become luminal cells or basal cells during normal breast development. In cancer, transcription factors can become deregulated, influencing what type of breast tumour will form. In aggressive basal-type breast tumours, SLUG is often over-expressed.

Previous work led by Charlotte Kuperwasser, principal investigator and senior author, determined that some common forms of breast cancer originate from luminal cells, whereas rare forms of breast cancer originate from basal cells. This difference in origins suggests that genes that affect the ability of a cell to become luminal or basal may also affect the formation of breast tumours. Because SLUG can regulate breast-cell differentiation, Kuperwasser’s team investigated SLUG’s role in breast-cell differentiation and tumor growth.

The research team reduced the expression of the SLUG gene in human-derived breast cells and then used cell-sorting techniques to separate the cells into groups of luminal, basal, and stem cells. Next, they used mathematical modelling to measure the rate and frequency that each of the three cell types changed into another cell type. By comparing the rates between control cells and cells in which SLUG was reduced, the team was able to determine the role of SLUG in luminal-, basal-, and stem-cell transitions.

To test the result of their mathematical model, the research team examined and compared breast-tissue samples from mice in two groups: a control group with normal SLUG and an experimental group that did not express SLUG. Mammary glands from the experimental and control groups were analyzed for changes in structure, the amount and distribution of luminal and basal cells in the gland, and whether these cells had stem-cell activity.

The SLUG-deficient mice exhibited defects in breast-cell differentiation. The mammary glands of these mice had too many luminal cells and defective basal cells that had luminal-cell characteristics. The control group of normal mice had a normal ratio of luminal to basal cells.

The SLUG-deficient mice showed defects in stem-cell function: Specifically, tumour formation and tissue regeneration was inhibited, an indication of defective stem cells, suggesting that SLUG was necessary to maintain normal luminal and basal cells within the mammary gland.

Additionally, SLUG-deficient cells when transplanted could not regenerate the mammary gland of the mouse, suggesting that SLUG is necessary for mammary stem-cell function. Tumour formation was also inhibited in SLUG-deficient mice, suggesting that SLUG may affect stem-cell activity necessary for tumour formation. Tufts University

Dartmouth Institute for Quantitative Biomedical Sciences (iQBS) researchers developed a new gene expression analysis approach for identifying cancer genes. The study results challenge the current paradigm of microarray data analysis and suggest that the new method may improve identification of cancer-associated genes.

Typical microarray-based gene expression analyses compare gene expression in adjacent normal and cancerous tissues. In these analyses, genes with strong statistical differences in expression are identified. However, many genes are aberrantly expressed in tumours as a byproduct of tumorigenesis. These ‘passenger’ genes are differentially expressed between normal and tumour tissues, but they are not ‘drivers’ of tumorigenesis. Therefore, better analytical approaches that enrich the list of candidate genes with authentic cancer-associated ‘driver’ genes are needed.

Lead authors of the study, Ivan P. Gorlov, PhD, Associate Professor of Community and Family Medicine and Christopher Amos, PhD, Professor of Community and Family Medicine and Director of the Center for Genomic Medicine described a new method to analyse microarray data. The research team demonstrated that ranking genes based on inter-tumour variation in gene expression outperforms traditional analytical approaches. The results were consistent across four major cancer types: breast, colorectal, lung, and prostate cancer.

The team used text-mining to identify genes known to be associated with breast, colorectal, lung, and prostate cancers. Then, they estimated enrichment factors by determining how frequently those known cancer-associated genes occurred among the top gene candidates identified by different analysis methods. The enrichment factor described how frequently cancer associated genes were identified compared to the frequency of identification that one could expect by pure chance. Across all four cancer types, the new method of selecting candidate genes based on inter-tumour variation in gene expression outperformed the other methods, including the standard method of comparing mean expression in adjacent normal and tumour tissues. Dr. Gorlov and colleagues also used this approach to identify novel cancer-associated genes.

The authors cite tumour heterogeneity as the most likely reason for the success of their variance-based approach. The method is based on the knowledge that different tumours can be driven by different subsets of cancer genes. By identifying genes with high variation in expression between tumours, the method preferentially identifies genes specifically associated with cancer. This same feature, tumour heterogeneity, may reduce the ability to identify critical gene expression changes when comparing mean gene expression in adjacent tumor and normal tissues, as tumors of the same type may have different sets of genes differentially expressed.

The results of the study challenge the model that comparing mean gene expression in adjacent normal and cancer tissues is the best approach to identifying cancer-associated genes. Indeed, the team identified high variation in adjacent ‘normal’ tissue samples, which are typically used as control samples for comparison in analyses based on mean gene expression. The study suggests that methods based on variance may help get the most from existing and future global gene expression studies. Dartmouth Institute for Quantitative Biomedical Sciences