Researchers turn to machines to identify breast cancer type

December 2, 2013

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 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 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 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."

Explore further: Mutations linked to breast cancer treatment resistance

More information: Their findings were published Dec. 2 in the peer-reviewed journal PLOS ONE.

Related Stories

Mutations linked to breast cancer treatment resistance

November 3, 2013
Researchers at the University of Michigan Comprehensive Cancer Center have identified a type of mutation that develops after breast cancer patients take anti-estrogen therapies. The mutations explain one reason why patients ...

Study finds new explanation for resistance to breast cancer treatment

November 13, 2013
Breast cancers that initially respond to hormone therapies such as tamoxifen eventually become resistant to treatment, and a new study finds this may be because of a mutation in the receptor present in the cancer cell to ...

The factor that could influence future breast cancer treatment

December 27, 2012
Australian scientists have shown in the laboratory how a 'transcription factor' causes breast cancer cells to develop an aggressive subtype that lacks sensitivity to estrogen and does not respond to known anti-estrogen therapies. ...

New driver of breast cancer discovered

November 7, 2013
A team of researchers at UT Southwestern has found that as cholesterol is metabolized, a potent stimulant of breast cancer is created – one that fuels estrogen-receptor positive breast cancers, and that may also defeat ...

Spread of breast cancer linked to kisspeptins which normally inhibit metastasis

April 16, 2013
KISS 1 is a metastasis-suppressor gene which helps to prevent the spread of cancers, including melanoma, pancreatic and ovarian cancers to name a few. But new research from Western University's Schulich School of Medicine ...

Genes identify breast cancer risk and may aid prevention

March 19, 2013
A newly identified set of genes may predict which women are at high risk for getting breast cancer that is sensitive to estrogen and, therefore, would be helped by taking drugs to prevent it, reports a new Northwestern Medicine ...

Recommended for you

Shooting the achilles heel of nervous system cancers

July 20, 2017
Virtually all cancer treatments used today also damage normal cells, causing the toxic side effects associated with cancer treatment. A cooperative research team led by researchers at Dartmouth's Norris Cotton Cancer Center ...

Molecular changes with age in normal breast tissue are linked to cancer-related changes

July 20, 2017
Several known factors are associated with a higher risk of breast cancer including increasing age, being overweight after menopause, alcohol intake, and family history. However, the underlying biologic mechanisms through ...

Immune-cell numbers predict response to combination immunotherapy in melanoma

July 20, 2017
Whether a melanoma patient will better respond to a single immunotherapy drug or two in combination depends on the abundance of certain white blood cells within their tumors, according to a new study conducted by UC San Francisco ...

Discovery could lead to better results for patients undergoing radiation

July 19, 2017
More than half of cancer patients undergo radiotherapy, in which high doses of radiation are aimed at diseased tissue to kill cancer cells. But due to a phenomenon known as radiation-induced bystander effect (RIBE), in which ...

Definitive genomic study reveals alterations driving most medulloblastoma brain tumors

July 19, 2017
The most comprehensive analysis yet of medulloblastoma has identified genomic changes responsible for more than 75 percent of the brain tumors, including two new suspected cancer genes that were found exclusively in the least ...

Novel CRISPR-Cas9 screening enables discovery of new targets to aid cancer immunotherapy

July 19, 2017
A novel screening method developed by a team at Dana-Farber/Boston Children's Cancer and Blood Disorders Center—using CRISPR-Cas9 genome editing technology to test the function of thousands of tumor genes in mice—has ...

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.