A new term in biophysics: force/time = "yank"

A group of scientists have proposed to define change in force over time as Read more

Are immune-experienced mice better for sepsis research?

The goal is to make mouse immune systems and microbiomes more complex and more like those in humans, so the mice they can better model the deadly derangement of Read more

One more gene between us and bird flu

We’re always in favor of stopping a massive viral pandemic, or at least knowing more about what might make one Read more

Cancer Genome Atlas

CAPTCHA some cancer cells

Humans are good at deciphering complex images, compared to computers. Until recently, internet users often needed to verify that they were human by completing a CAPTCHA security check. A familiar variety asked the user to check all the boxes that contain a car, or a street sign.

If we asked random people off the street to look at pathology slides and “quick, check all the boxes that contain tumor cells,” what would happen? The accuracy, compared to a trained pathologist, wouldn’t be very good.

Not as easy as labeling which boxes contain street signs!

This challenge of expertise – crowdsourcing and pathology are not immediately compatible – is what Lee Cooper and colleagues sought to overcome in a recent paper published in Bioinformatics. So they put together something they called “structured crowdsourcing.”

“We are interested in describing how the immune system behaves in breast cancers, and so we built an artificial intelligence system to look at pathology slides and identify the tissue components,” Cooper says.

His group was particularly interested in the aggressive form of breast cancer: triple negative. They used pathology slide images from the Cancer Genome Atlas, a National Cancer Institute resource. The goal was to mark up the slides and label which sections contained tumor, stroma, white blood cells, dead cells etc.

They used social media to recruit 25 volunteers — medical students and pathologists from around the world (Egypt, Bangladesh, Saudi Arabia, United Arab Emirates, Syria, USA). Participants underwent training and used Slack to communicate and learn about how to classify images. They collaborated using the Digital Slide Archive, a tool developed at Emory. Read more

Posted on by Quinn Eastman in Cancer Leave a comment

Blocking glioblastoma escape

Treatment strategies for several types of cancer have been transformed by the discovery of “targeted therapies,” drugs directed specifically against the genetic mutations that drive tumor growth. So far, these strategies have been relatively unsuccessful when it comes to glioblastoma, the most common and most deadly form of brain tumor affecting adults. Glioblastoma was one of the first tumor types to be analyzed in the Cancer Genome Atlas mega-project, but many of the molecular features of glioblastoma have been difficult to exploit.

For example, about 40 percent of glioblastoma tumors ray ban baratas have extra copies of the EGFR (epidermal growth factor receptor) gene. EGFR provides a pedal-to-the-metal growth signal and is known to play a role in driving the growth of lung and colon cancers as well. But drugs targeted against EGFR that have extended patient survival in lung cancer have shown disappointing results with glioblastoma. The reason: the tumor cells can quickly mutate the EGFR gene or switch to reliance on other growth signals.

Keqiang Ye, PhD and colleagues recently described the discovery of a compound that may be valuable in fighting glioblastoma. The Emory researchers devised a scheme to stop tumor cells from using well-known escape routes to avoid EGFR-based drugs. Their results are published in the journal Science Signaling. Postdoctoral fellow Kunyan He, PhD, is the first author.

The compound they identified inhibits the enzyme JAK2, one of the apparent escape Ray Ban outlet routes taken by glioblastoma cells. The compound can pass the blood-brain barrier and inhibit glioblastoma growth while having low toxicity, the researchers report.

Posted on by Quinn Eastman in Cancer 1 Comment

What cancer researchers can learn from fruit fly genetics

What can scientists studying cancer biology learn from fruit flies?

Quite a lot, it turns out.  At a time when large projects such as the Cancer Genome Atlas seek to define the changes in DNA that drive cancer formation, it is helpful to have the insight gained from other arenas, such as fruit flies, to make sense of the mountains of data.

Drosophila melanogaster has been an important model organism for genetics because the flies are easy to care for, reproduce rapidly, and have an easily manipulated genome. This NCI newsletter article describes how some investigators have used Drosophila to find genes involved in metastasis.

Emory cell biologist Ken Moberg says that he and postdoctoral fellow Melissa Gilbert crafted a Drosophila-based strategy to identify growth-regulating genes that previous researchers may have missed. Their approach allowed them to begin defining the function of a gene that is often mutated in lung cancer. The results are published online in Developmental Cell.

Part of the developing fly larva, stained with an antibody against Myopic. Groups of cells lacking Myopic, which lack green color, tend to divide more rapidly.

Moberg writes:

Many screens have been carried out in flies looking for single gene lesions that drive tissue overgrowth. But a fundamental lesson from years of cancer research is that many, and perhaps most, cancer-causing mutations also drive compensatory apoptosis, and blocking this apoptosis is absolutely required for cancer outgrowth.

We reasoned that this class of ‘conditional’ growth suppressor genes had been missed in prior screens, so we designed an approach to look for them. The basic pathways of apoptosis are fairly well conserved in flies, so it’s fairly straight forward to do this.

Explanatory note: apoptosis is basically a form of cellular suicide, which can arise when signals within the cell clash; one set of proteins says “grow, grow” and another says “brake, brake,” with deadly results.

Gilbert identified the fruit fly gene Myopic as one of these conditional growth regulators. She used a system where mutations in Myopic drive some of the cells in the fly’s developing eye to grow out more – but only when apoptosis is disabled.

Gilbert showed that Myopic is part of a group of genes in flies, making up the Hippo pathway, which regulates how large a developing organ will become. This pathway was largely defined in flies, then tested in humans, Moberg says. The functions of the genes in this pathway have been maintained so faithfully that in some cases, the human versions can substitute for the fly versions.

Myopic’s ortholog (ie different species, similar sequence and function) is the gene His-domain protein tyrosine phosphatase, or HD-PTP for short. This gene is located on part of the human genome that is deleted in more than 90 percent of both small cell and non-small cell lung cancers, and is also deleted in renal cancer cells.

How HD-PTP, when it is intact, controls the growth of cells in the human lung or kidney is not known. Gilbert and Moberg’s findings suggest that HD-PTP may function through a mechanism that is similar to Myopic’s functions in the fly.

Besides clarifying what Myopic does in the fly, their paper essentially creates a map for scientists studying HD-PTP’s involvement in lung cancer, for example, to probe and validate.

Posted on by Quinn Eastman in Cancer 1 Comment