Saturday May 25, 2019

Common Diabetes Drug May Offer Treatment For Breast Cancer, Says Study

However, neither of the drugs were originally designed to treat cancer

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Cancer
Cancer Ribbon. Pixabay
Repurposing a common diabetes drug as well as another used for treating a group of inherited and acquired disorders may also help in the fight against resistant breast cancers that currently have no targeted therapy, finds a study.
The study, led by the University of Chicago, showed that the two existing drugs named metformin and haemin suppress tumour growth in mice, Xinhua reported.
“This is the first joint use of these two drugs. We think we have elucidated a new mechanism, something basic and fundamental, and found ways to use it,” said Marsha Rosner, Professor at the varsity.
The researchers found that the primary anti-cancer target for haemin is a transcription factor known as BACH1 (BTB and CNC homology1). This protein is often highly expressed in triple negative breast cancers and is required for metastasis.
BACH1 targets mitochondrial metabolism and can suppress a key source of cellular energy. When BACH1 is high, this energy source is shut down, the report said.
However, when cancer cells were treated with haemin, BACH1 was reduced, causing BACH1-depleted cancer cells to change metabolic pathways. This caused cancers that are vulnerable to metformin to suppress mitochondrial respiration.
Diabetes
Representational image. Pixabay
“We found that this novel combination, haemin plus metformin, can suppress tumour growth, and we validated this in mouse tumour models,” explained Jiyoung Lee from the varsity.
The findings can extend beyond breast cancer.
BACH1 expression is enriched not only in triple negative breast cancers, but is also seen in many other cancers including lung, kidney, uterus, prostate and acute myeloid leukemia, the researchers noted.
However, neither of the drugs were originally designed to treat cancer.
Metformin, discovered in 1922 and used clinically since 1957, was developed to treat Type-2 diabetes. It decreases glucose production by the liver and increases insulin sensitivity.
Haemin, marketed as panhematin, was first crystallised from blood in 1853. It is now used to treat defects of haemin synthesis. These defects can cause porphyrias, a group of inherited and acquired disorders. (IANS)

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Novel AI Method Predicts Future Risk of Breast Cancer

The advantages held across different subgroups of women, said the study published in the journal Radiology

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Cancer
Cancer Ribbon. Pixabay

Researchers have developed a new tool with advanced artificial intelligence (AI) methods to predict a woman’s future risk of breast cancer.

For the study, the researchers used almost 90,000 full-resolution screening mammograms from about 40,000 women to train, validate and test the deep learning model.

“There’s much more information in a mammogram than just the four categories of breast density, “said study lead author Adam Yala from the Massachusetts Institute of Technology (MIT) in the US.

“By using the deep learning model, we learn subtle cues that are indicative of future cancer,” Yala added.

The research team recently compared three different risk assessment approaches. The first model relied on traditional risk factors, the second on deep learning that used the mammogram alone, and the third on a hybrid approach that incorporated both the mammogram and traditional risk factors into the deep learning model.

Cancer patient
Cancer patient.

The deep learning models yielded substantially improved risk discrimination over the Tyrer-Cuzick model, a current clinical standard that uses breast density in factoring risk.

When comparing the hybrid deep learning model against breast density, the researchers found that patients with non-dense breasts and model-assessed high risk had 3.9 times the cancer incidence of patients with dense breasts and model-assessed low risk.

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The advantages held across different subgroups of women, said the study published in the journal Radiology.

“Unlike traditional models, our deep learning model performs equally well across diverse races, ages and family histories,” said Regina Barzilay, Professor at MIT. (IANS)