Researchers turn to machines to identify breast cancer type

December 02, 2013

(Edmonton) Researchers from the University of Alberta and Alberta Health Services have created a computer algorithm that successfully predicts whether estrogen is sending signals to cancer cells to grow into tumours in the breast. By finding this hormone receptor, known as estrogen receptor positive, physicians can prescribe anti-estrogen drug therapies, improving patient outcomes.

Since each cell in the body contains 23,000 genes, identifying the specific genes involved in cancer growth is an exceedingly complex task. Researchers used a form of artificial intelligence called machine learning to identify three genes that allowed them to determine whether a tumour was fed by estrogen.

"People can't possibly sort through all this information and find the important patterns," said senior author Russ Greiner, a professor in the Department of Computing Science and investigator with the Alberta Innovates Centre for Machine Learning. "Machines have other limitations, but what they can do is go through high-dimensional data. With our techniques, we can find combinations of biomarkers that can predict important properties of specific breast cancers."

Greiner's team created an algorithm that proved 93 per cent accurate in predicting the estrogen receptor status of tumours. To do this, they relied on data gathered from 176 frozen tumour samples stored at the Canadian Breast Cancer Foundation Tumor Bank at the Cross Cancer Institute in Edmonton.

The same algorithm was later tested on other data sets available online, with similar success. The results were cross-checked with existing tests done by pathologists using traditional estrogen-receptor testing.

"Essentially, we've identified something inexpensive and simple that could replace receptor testing done in a clinical lab," said co-author John Mackey, director of Cross Cancer Institute Clinical Trials Unit, Alberta Health Services. "This is a new way of sifting through thousands of signals and pulling out the wheat from the chaff. In principle, this could be applied to other biomarkers and distil data down into something that a clinician can use."

Mackey, who is also a professor of medical oncology with the Faculty of Medicine & Dentistry, said the technique is poised to take advantage of new gene-sequencing technologies, or genomics, which aims to understand the inner workings of cancer cells with a goal of tailoring treatments for individual patients.

It's still premature to consider the algorithm as a replacement for traditional lab tests, but that could change as new technologies become more affordable, perhaps in five to eight years.

"We're not there yet, but at some point it's going to be cheaper to take a tumour and put it into the machine and get these thousands of signals about its biology than it is to do the increasing number of required tests using traditional techniques in a lab," Mackey said. "When those two lines intersect, we're going to switch to using the new technologies, and we will need algorithms like this to make sense of the data."
-end-
The research team also included Meysam Bastani, Larissa Vos, Nasimeh Asgarian, Jean Deschenes and Kathryn Graham. Their findings were published Dec. 2 in the peer-reviewed journal PLOS ONE.

University of Alberta

Related Cancer Cells Articles from Brightsurf:

Cancer researchers train white blood cells to attacks tumor cells
Scientists at the National Center for Tumor Diseases Dresden (NCT/UCC) and Dresden University Medicine, together with an international team of researchers, were able to demonstrate that certain white blood cells, so-called neutrophil granulocytes, can potentially - after completing a special training program -- be utilized for the treatment of tumors.

New way to target some rapidly dividing cancer cells, leaving healthy cells unharmed
Scientists at Johns Hopkins Medicine and the University of Oxford say they have found a new way to kill some multiplying human breast cancer cells by selectively attacking the core of their cell division machinery.

Breast cancer cells use message-carrying vesicles to send oncogenic stimuli to normal cells
According to a Wistar study, breast cancer cells starved for oxygen send out messages that induce oncogenic changes in surrounding normal epithelial cells.

Breast cancer cells turn killer immune cells into allies
Researchers at Johns Hopkins University School of Medicine have discovered that breast cancer cells can alter the function of immune cells known as Natural killer (NK) cells so that instead of killing the cancer cells, they facilitate their spread to other parts of the body.

Breast cancer cells can reprogram immune cells to assist in metastasis
Johns Hopkins Kimmel Cancer Center investigators report they have uncovered a new mechanism by which invasive breast cancer cells evade the immune system to metastasize, or spread, to other areas of the body.

Engineered immune cells recognize, attack human and mouse solid-tumor cancer cells
CAR-T therapy has been used successfully in patients with blood cancers such as lymphoma and leukemia.

Drug that keeps surface receptors on cancer cells makes them more visible to immune cells
A drug that is already clinically available for the treatment of nausea and psychosis, called prochlorperazine (PCZ), inhibits the internalization of receptors on the surface of tumor cells, thereby increasing the ability of anticancer antibodies to bind to the receptors and mount more effective immune responses.

Engineered bone marrow cells slow growth of prostate and pancreatic cancer cells
In experiments with mice, researchers at the Johns Hopkins Kimmel Cancer Center say they have slowed the growth of transplanted human prostate and pancreatic cancer cells by introducing bone marrow cells with a specific gene deletion to induce a novel immune response.

First phase i clinical trial of CRISPR-edited cells for cancer shows cells safe and durable
Following the first US test of CRISPR gene editing in patients with advanced cancer, researchers report these patients experienced no negative side effects and that the engineered T cells persisted in their bodies -- for months.

Zika virus' key into brain cells ID'd, leveraged to block infection and kill cancer cells
Two different UC San Diego research teams identified the same molecule -- αvβ5 integrin -- as Zika virus' key to brain cell entry.

Read More: Cancer Cells News and Cancer Cells Current Events
Brightsurf.com is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to Amazon.com.