Posts Tagged ‘dna’

New method for non-invasive prostate cancer screening

Now a team of researchers led by Shaoxin Li at Guangdong Medical College in China has demonstrated the potential of a new, non-invasive method to screen for prostate cancer, a common type of cancer in men worldwide. They describe their laboratory success testing an existing spectroscopy technique called surface-enhanced Raman scattering (SERS) with a new, sophisticated analysis technique called support vector machine (SVM).

As they described in a new paper in Applied Physics Letters, from AIP Publishing, they combined SERS and SVM and applied them to blood samples collected from 68 healthy volunteers and 93 people who were clinically confirmed to have prostate cancer. They found their technique could identify the cases of cancer with an accuracy of 98.1 percent.

If the technique proves safe and effective in clinical trials, it may become a new method available to patients and their doctors, helping to improve the early detection and diagnosis of this type of cancer, said Li.

“The results demonstrate that label-free serum SERS analysis combined with SVM diagnostic algorithm has great potential for non-invasive prostate cancer screening,” said Li. “Compared to traditional screening methods, this method has the advantages of being non-invasive, highly sensitive and very simple for prostate cancer screening.”

A COMMON CAUSE OF CANCER

According to the World Health Organization, prostate cancer is one of the most common types of cancer in men worldwide and a leading cause of cancer-related death. Every year, there are about 899,000 new cases and 260,000 mortalities, comprising 6 percent of all cancer deaths globally. About 1 in every 6 men will develop prostate cancer over their lifetimes.

While a simple blood test for elevated levels of a protein marker known as prostate specific antigen (PSA) has been used for years to screen for early cases of prostate cancer, the test is far from perfect because the elevated PSA levels can be caused by many things unrelated to cancer. This contributes to over-diagnosis, uncomfortable tissue biopsies and other unnecessary treatment, which can be costly and carry significant side effects. Because of this, the U.S. Preventative Services Task Force now recommends against PSA-based screening for prostate cancer.

According to Li, many scientists have thought about applying SERS to cancer detection because the surface-sensitive type of spectroscopy has been around for years and is sensitive enough to identify key molecules in very low abundance, like pesticide residues on a contaminated surface. This would seem to make it perfect for spotting subtle signals of DNA, proteins or fatty molecules that would mark a case of cancer — exactly why he and his team tackled the problem.

The challenge, he said, was that these changes were, if anything, too subtle. The signal differences between the serum samples taken from the 68 healthy volunteers and the 93 people with prostate cancer were too tiny to detect. So to accurately distinguish between these samples, Li’s group employed a powerful spectral data processing algorithm, support vector machine (SVM), which effectively showed the difference.

While the work is preliminary, it shows that serum SERS spectroscopy combined with SVM diagnostic algorithm has the potential to be a new method for non-invasive prostate cancer screening, Li said. The next research step, he added, is to refine the method and explore whether this method can distinguish cancer staging.

source : http://www.sciencedaily.com/releases/2014/09/140902114041.htm

‘K-to-M’ Histone Mutations: How Repressing Repressors May Drive Tissue-Specific Cancers

In 2012, investigators from multiple research institutions studying the sequence of the genome from cancer patients rocked the “chromatin world” when they independently reported that mutations in the gene that encodes histone H3.3 occurred in aggressive pediatric brain tumors. This finding was stunning, as researchers had never before associated histone mutations with any disease, much less a deadly tumor. What followed was a race by cancer researchers worldwide to discover how histone mutations might promote tumorigenesis.

Now a paper from a laboratory at the Stowers Institute of Medical Research reports the first animal model created to assess the molecular effects of two different histone H3.3 mutations in the fruit fly Drosophila. The study from a team led by Investigator Ali Shilatifard, Ph.D. published in the August 29, 2014 issue of Science, strongly suggests that these mutations actually could drive cancer and identifies interacting partners and pathways that could be targeted for the treatment of cancer.

Molecular biologists categorize these mutations as “K-to-M,” because a normal lysine residue (symbolized by K) in the protein is replaced by methionine (M) through mutations in the DNA sequence. In pediatric tumors, K-to-M mutations occurred at lysine residue 27 (K27) of histone H3.3. Researchers suggested that the presence of even a small population of these damaged proteins in the nucleus muffled a large repressor complex called PRC2. Normally, PRC2 acts as an enzyme to decorate histone lysines with one or more methyl groups, which silences gene expression by squeezing associated DNA into an impenetrable coil.

“Previously scientists knew that mutations in methylating enzymes like PRC2 occur in some cancers,” says Shilatifard. “What was surprising here was finding that mutation in one of the copies of the histone H3 gene, one of the proteins that PRC2 modifies, is associated with cancer. To figure out how that happened, we were interested in developing an in vivo model for the process in systems that we can study.”

The team first engineered a version of histone H3.3 that mimicked the K27-to-M mutation and then inserted that construct into embryonic fly tissues to produce the damaged protein in a living fruit fly. Using antibodies that recognize methylated lysines, they discovered that a dose of the mutant protein was sufficient to decrease global methylation of normal histone H3.3 proteins at K27, just as loss of the PRC2 repressor would. When the group engineered a similar K-to-M mutant at lysine 9 (K9), they saw similar results. This analysis of the H3K27 and H3K9 mutants confirmed in vivo that K-to-M mutations in histone H3.3 repress a key repressor, PRC2, but did not nail down how this happened.

“One question was whether a single amino acid change like this could alter the way histone H3.3 interacts with other proteins,” says Marc Morgan, Ph.D., a co-first author of the paper, “The mutant could be either losing or gaining something.” To determine which, the group collaborated with the Stowers Proteomics Center to compare factors binding to normal histone H3.3 versus the K-to-M mutants using mass spectrometry.

That analysis revealed that the presence of mutant histones globally dampens histone interactions with some of the usual repressor suspects. But in what Morgan calls an “Aha!” moment, they detected promiscuous association of a demethylase called KDM3B with the histone H3K9 mutant. “This suggests that these mutations inappropriately pull a demethylating enzyme onto chromatin, which then erases methylation marks in histones around it,” Morgan says.

Loss of methylation marks could allow expression of nearby genes. To confirm this, the group employed a Drosophila staining trick that allows experimenters to visualize how repressed genes are affected in entire tissues. The expression of KDM3B demethylase derepressed the gene expression in tissues such as salivary glands, just like the expression of the H3K9 mutant. This supports the idea that K-to-M mutations recruit a demethylase (like KDM3B) to demethylate chromatin on the K9 residue of H3.3 proteins in the neighborhood, where it likely uncoils chromatin to allow activation of genes that should be silenced.

This outcome could cause cancer in numerous ways. “One possibility might be that oncogenes that are usually silenced by methylation of residue 9 might be derepressed in the presence of the mutation,” says Hans-Martin Herz, Ph.D., a co-first author of the paper. But Herz is cautious in interpreting these findings, simply because, unlike the K27 mutations, mutations at residue K9 are not yet reported to be associated with cancer.

Intriguingly, other researchers recently reported a different K-to-M mutation (at residue 36 of histone H3.3) in chondroblastoma, a bone cancer sub-type. Why K-to-M mutations are so specific to a particular cancer is unknown, but Shilatifard says there can be little doubt that they play a central rather than a bystander role in tumorigenesis. “Uncharacterized K-to-M mutations may occur in other cancers,” he says. “Our work allows us to identify the molecular players involved in chromatin signaling in Drosophila and then apply those findings to human cells.”

source : http://www.sciencedaily.com/releases/2014/08/140829103216.htm

Statistical Approach for Calculating Environmental Influences in Genome-Wide Association Study (GWAS) Results

The approach fills a gap in current analyses. Complex diseases like cancer usually arise from complex interactions among genetic and environmental factors. When many such combinations are studied, identifying the relevant interactions versus those that reflect chance combinations among affected individuals becomes difficult. In this study, the investigators developed a novel approach for evaluating the relevance of interactions using a Bayesian hierarchal mixture framework. The approach is applicable for the study of interactions among genes or between genetic and environmental factors.

Chris Amos, PhD, senior author of the paper said, “These findings can be used to develop models that include only those interactions that are relevant to disease causation, allowing the researcher to remove false positive findings that plague modern research when many dozens of factors and their interactions are suggested to play a role in causing complex diseases.”

The model evaluates “gene by gene” and “gene by environment” factors by looking at specific DNA sequencing variations. Complex diseases are caused by multiple factors. In some cases a genetic predisposition or abnormality may be a factor. A person’s healthy lifestyle and environment, however, may help him or her overcome a genetic vulnerability and avoid a chronic disease like cancer. In other situations, a person whose DNA does not have an abnormality may develop one when exposed to known carcinogens like tobacco smoke or sunburn.

“Understanding the combinations of genetic and environmental factors that cause complex diseases is important,” said Amos, associate director of population sciences and deputy director of Norris Cotton Cancer Center, “because understanding the genetic architecture underlying complex disease may help us to identify specific targets for prevention or therapy upon which interventions may appropriately reduce the risk of cancer development or progression.”

The study applied the model in cutaneous melanoma and lung cancer genetic sequences using previously identified abnormalities (known as single nucleotide polymorphisms or SNPs) with environmental factors introduced as independent variables. The Bayesian mixture model was compared with the traditional logistic regression model. The hierarchal model successfully controlled the probability of false positive discovery and identified significant interactions. It also showed good performance on parameter estimation and variable selection. The model cannot be applied to a complete GWAS because if its reliance on other probability models (MCMC ). It is most effective when applied to a group of SNPs.

“The method was effective for the study of melanoma and lung cancer risk because these cancers develop from a complex interaction between genetic and environmental factors but understanding how these factors interact has been difficult to achieve without the sophisticated modeling that has been developed in this study,” said Amos.

source : http://www.sciencedaily.com/releases/2014/08/140827111811.htm