AI maps tumor cells, blood filters save children

Two medical innovations announced this week could reshape how doctors fight cancer and sepsis, the conditions for hundreds of thousands of lives each year.

At Yale, researchers have launched an AI tool that maps the hidden diversity of tumor cells, while Michigan medical doctors use experimental filtering devices to save children with a 5% chance of survival.

Both advances address a fundamental challenge in medicine: understanding complex diseases vary from patient to patient, even from cell to cell.

These developments highlight how precision medicine can transcend a therapy suitable for a variety of treatments – towards a therapy tailored to a single biological feature.

Decode the cellular chaos of cancer

Tumors are not the unified mass of the same cells, they are chaotic communities, with different cell populations behaving in completely different ways. This cellular diversity makes it difficult to completely treat cancer.

“Heterogeneity is a problem because at present, we think of tumors as being made up of the same cell,” explains Christine Chaver, a co-training co-director of the Yale-led Research and co-director of the Cancer Plasticity and Dormancy Program at the Galwan Medical Institute. “Although the patient may have an initial response, the remaining cells can grow and the cancer may recover.”

An AI tool called AANET analyzes gene expression patterns in individual tumor cells to identify five different cell “prototypes” – with different growth patterns, metastatic potential and therapeutic vulnerability. The study focuses on cancer models, but may extend to other cancers.

Blood cleaning device violates odds

Meanwhile, in Michigan Medicine, doctors face different life or death situations. A young patient with a previous kidney transplant suffered from leukemia and then suffered from septic shock of five organ failure after chemotherapy. Traditional treatments don’t work.

“When we intervened, the patient was almost 100% more likely to die,” recalls David Humes, MD, a MD, who spent 20 years developing an experimental filter device.

The selective cellular biological device works like a professional dialysis machine, before pumping blood into the blood outside the body and “calm” overactive immune cells, then returning it to the patient. In sepsis, the immune system often attacks healthy organs while trying to fight infection, which can be a fatal inflammatory response.

Precise methods to solve complex problems

Both innovations involve the same core challenge: the biological complexity of violating simple solutions.

Key effects of the study:

• AANET identified five cancer cell prototypes with unique therapeutic vulnerabilities
• Hemofiltration reverses multi-organ failure in patients with neutropenia
• Both technologies target cell-level differences, rather than broad disease categories
• Clinical trials are expanding to multiple medical centers

Cancer AI tools can fundamentally change treatment options. “Currently, cancer treatment options for patients are based primarily on the cancer’s organs from breast cancer, lungs or prostate,” Chaffer noted. Instead, the tool focuses on the work that each group of cells actually does biologically.

Technology meets human bets

Both stories emphasize how cutting-edge technologies translate into human achievements. Children in Michigan entered the hospital with a 5% chance of survival and spent 38 days before intensive care without cancer. AI cancer tools offer hope for patients with drug-resistant cells in tumors.

“Thanks to advances in technology, data explosions have been seen at the single-cell level over the past 20 years,” observed Smita Krishnaswamy, associate professor of computer science and genetics at Yale School of Medicine. “We have been finding that not only does each patient have different cancers, but each cancer cell behaves differently than another.”

Both technologies have been extended beyond their initial applications. Filter devices are being used in multiple pediatric sites, and cancer AI tools show hope for autoimmune diseases. As Garvan Chief Sarah Kummerfeld noted: “We envision a future where doctors combine this AI analysis with traditional cancer diagnosis to develop more personalized treatments to target all cell types in a person’s unique tumor.”

Related