Reprogramming breast cancer
UND Department of Biomedical Sciences researcher Motoki Takaku tackles the reverse engineering of cancer
Given his calm voice and reserved demeanor, one might get the impression that the science he was describing was really no big deal.
“We realized that in terminally differentiated cells, you can turn them back to the original embryonic stem cells,” smiled Dr. Motoki Takaku from his office at the UND School of Medicine & Health Sciences (SMHS), referencing Shinya Yamanaka’s work on the “reprogramability” of mature human cells. “Cells that seem static are actually very dynamic. By modulating their governing structure, you can change any cell into any other kind of cell.”
So, suggested the assistant professor in the SMHS Department of Biomedical Sciences, epithelial cells, for example, can be reverse engineered into neurons.
This paradigm-shifting discovery, which resulted in Yamanaka’s winning the Nobel Prize in Medicine in 2012, is especially significant for researchers studying a variety of cancers, said Takaku, citing the statistic that one in eight women in the United States will be diagnosed with breast cancer in her lifetime.
“The same reprogramming concept can be applied to cancer cells,” he explained of his epigenetic project. “When the cancer cells become very aggressive, you should be able to turn them back into the non-cancerous state again. What we’re trying to do here is to understand how to change these cells’ fate.”
Density is destiny
At the core of this potentially revolutionary alterability of cell fate is a cellular substance called chromatin, Takaku continued, which helps govern how densely compacted DNA is within cells. This relative density – and/or laxity – affects stem cells’ destiny, it seems, helping determine whether they become osteocytes or neurons, epidermal cells or lymphocytes.
Understanding better the interplay between chromatin and breast cancer cells is the goal of Takaku’s recently awarded R01 grant from the National Institutes of Health (NIH) – the highest biomedical grant the institution gives out.
“This knowledge is very important for both basic study and any clinical studies – so that we can understand, whenever we get any disease, why these cells are behaving weirdly or not doing their job,” said Takaku, making air quotation marks with his hands. “If we have ability to convert cells back to the ‘normal’ state, we should be able to deal with many different kinds of disease.”
In the case of breast cancer, said Takaku, this reprogramming seems to be connected to one specific gene, GATA3, alterations and mutations of which seem to have important consequences for the cancer’s progression.
“This is a kind of one-cell ‘deprogramming’ system that we have been using,” said Takaku.
To clarify, there are really two issues at play: whether cancer cells can be reprogrammed in the first place. And if so, what effect this reprogramming, via GATA3, has on cancer.
This brings Takaku to his second recent grant.
As the researcher who came to UND from the NIH in 2019 explained, because more than 10% of breast tumors across demographic groups carry a mutation in the GATA3 gene that affects the severity of an individual’s breast cancer, his lab is also managing an American Cancer Society (ACS) grant exploring the manipulation of GATA3 in the context of prevention or potential treatment for breast cancer specifically.
While researchers understand that GATA3 is important in cancer, that is, they’re not certain of the gene’s role before and during tumorigenesis – or how the mutation impacts how aggressive a particular breast cancer will be and how the disease will progress.
To this end Takaku’s team is collecting experimental evidence on a variety of GATA3 mutant breast cancer cells for ACS to better understand the role of GATA3 in breast cancer.
Putting both grants together, Takaku said that his hope is to help determine if there are certain patients or patient cohorts for whom chemotherapy might be avoided. In such cases, oncologists could instead manipulate the GATA3 gene to slow, if not stop, the progression of breast cancer.
“But it’s not so simple,” Takaku cautioned. “In some cases, GATA3 mutations produce a much better prognosis. So, patients tend to live longer, or may even be disease free. But some groups of GATA3 mutations seem to produce bad cellular function, where the patient has a much worse prognosis.”
The challenge, said the researcher, is that “we don’t really understand why similar mutations in the same gene can produce these two very different patient outcomes.”
AI for cancer
This is where artificial intelligence might hold the key.
Adding that his team is putting out “all our experimental leads” via AI to train machines to learn to predict what is happening during this cellular reprogramming, Takaku explained that, in time, AI software might be able to interpret a complex set of data to predict alterations in cellular characteristics. Such learning could be applied to one breast cancer patient, for example, whose GATA3 expression – and thus treatment regimen – might differ from her cohorts.
“If you take blood and purify the DNA from the healthy donor, you can see some signs of immune cells in the blood,” Takaku continued. “However, if you take blood from a breast cancer patient, we can actually see signs of breast cancer in the blood. We can identify the breast cancer-specific mutations and can see the breast cancer-specific DNA structure in the blood. So, if we compare this information from healthy donors with breast cancer donors, we should be able to train AI to identify what is healthy tissue versus cancerous tissue – and whether or not the treatments used to attack or alter the cancer cells are working, or will even work at all.”
In other words, if AI can be trained to better identify “blood DNA” biomarkers among breast cancer patients, it might learn to distinguish which patients are sensitive to various chemotherapies even before they are used, avoiding some unnecessary and unpleasant treatments in advance and get to more effective treatments sooner.
“Hopefully, by simply using the patients’ blood,” said Takaku, his voice getting more animated now, “we might be able to distinguish those drug sensitivities, which will help guide the cancer treatment.”
And that is a big deal.