UM researchers use AI to understand the susceptibility of lung cancer cells
MISSOULA – A scientific team that includes University of Montana biologist Mark Grimes recently used artificial intelligence to better understand how groups of proteins in lung cancer cells regulate cell division and metabolism.
MISSOULA – A scientific team that includes University of Montana biologist Mark Grimes recently used artificial intelligence to better understand how groups of proteins in lung cancer cells regulate cell division and metabolism.
This work may lead to a greater understanding of lung cancer susceptibility and future anti-cancer therapies. The findings were published in PLOS Computational Biology.
“We examined how cells respond to anticancer drugs used to treat lung cancer,” said Grimes. “We use machine learning algorithms to detect patterns in data that are difficult to see because our human brains are not very good at seeing patterns in large spreadsheets.”
He said lung cancer was still the leading cause of death. New drugs to treat lung cancer may work temporarily, but cancer cells can develop and form new tumors, causing recurrences. To solve this problem, attacking cancer cells with a combination of drugs could work, but only if researchers gain a better understanding of the cancer cell’s weak points.
“The great thing about this work is we’ve turned the patterns we found into networks that represent cell signaling pathways affected by cancer mutations and drugs that target mutated genes, which are called oncogenes,” Grimes said. “This work takes this approach to the next level by looking at interactions between pathways, which are groups of proteins that work together in cells.”
He said this gave the research team a high-level, molecular-level view of the interactions between the pathways that cause cancer cells to divide and regulate their metabolism.
Grimes said cancerous tumors often have a hyperactive metabolism and limited oxygen supply.
“So identifying links between these pathways presents an opportunity to link susceptibility in import and utilization of nutrients in combination with other anticancer therapies.”
Other partners in this research include Georgetown University; Moffit Hospital in Tampa, Florida; and the University of Manitoba.
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Article title
Network model of protein phosphorylation, acetylation, and ubiquitination linking cell signaling pathways and metabolism in lung cancer
Article Publication Date
30-Mar-2023
