healthcare technology

“If you’re dealing with a disease like cancer that can be arrived at by multiple pathways, it makes sense that you’re not going to find that each patient has taken the same path” - John McDonald, a professor in the School of Biology at the Georgia Institute of Technology in Atlanta.

If a driver is traveling to New York City, I-95 might be their route of choice. But they could also take I-78, I-87 or any number of alternate routes. Most cancers begin similarly, with many possible routes to the same disease. A new study found evidence that assessing the route to cancer on a case-by-case basis might make more sense than basing a patient’s cancer treatment on commonly disrupted genes and pathways.

The study found little or no overlap in the most prominent genetic malfunction associated with each individual patient’s disease compared to malfunctions shared among the group of cancer patients as a whole.
“This paper argues for the importance of personalized medicine, where we treat each person by looking for the etiology of the disease in patients individually,” said McDonald, 

“The findings have ramifications on how we might best optimize cancer treatments as we enter the era of targeted gene therapy.”

The research was published February 11 online in the journal PANCREAS and was funded by the Georgia Tech Foundation and the St. Joseph’s Mercy Foundation.

In the study, researchers collected cancer and normal tissue samples from four patients with pancreatic cancer and also analyzed data from eight other pancreatic cancer patients that had been previously reported in the scientific literature by a separate research group.

McDonald’s team compiled a list of the most aberrantly expressed genes in the cancer tissues isolated from these patients relative to adjacent normal pancreatic tissue.

The study found that collectively 287 genes displayed significant differences in expression in the cancers vs normal tissues. Twenty-two cellular pathways were enriched in cancer samples, with more than half related to the body’s immune response. The researchers ran statistical analyses to determine if the genes most significantly abnormally expressed on an individual patient basis were the same as those identified as most abnormally expressed across the entire group of patients.

The researchers found that the molecular profile of each individual cancer patient was unique in terms of the most significantly disrupted genes and pathways.

more at http://www.news.gatech.edu/2014/02/24/personalized-medicine-best-way-treat-cancer-study-argues

Researchers uncover new ties between genetics and skin cancer by mining patients’ medical records.

Usually, studying the relationship between DNA and disease involves comparing the genomes of thousands of people with a disorder to the genomes of thousands of people who don’t. These studies can be expensive and may take years, requiring researchers to identify patients, enroll them in the study, and collect the genomic data.

Monitoring social media websites like Twitter could help health officials and providers identify in real time severe medical outbreaks, allowing them to more efficiently direct resources and curb the spread of disease, according to a San Diego State University studypublished last month in the Journal of Medical Internet Research,Medical News Today reports.

Study Details

For the study, lead researcher and San Diego State University geography professor Ming-Hsiang Tsou and his team used a program to monitor tweets that originated within a 17-mile radius of 11 cities. The program recorded details of tweets containing the words "flu" or "influenza," including:

• Origin;
• Username;
• Whether the tweet was an original or a retweet; and
• Any links to websites in the tweet.

Researchers then compared their findings with regional data based on CDC's definition of influenza-like illness.