Researchers at Vanderbilt University Medical Center using artificial intelligence have helped develop two technologies for improving cancer care. 

One technology called MSI-SEER, described in a study published in npj Digital Medicine, better predicts microsatellite instability-high status from standard pathology slides and provides clinicians with specific data, including any uncertainties with predictions. The other technology, a breakthrough three-dimensional imaging tool described in a study published in Nature Communications, has transformative potential beyond cancer diagnostics. 

These new technologies showcase how VUMC researchers are using the power of AI to meet a wide range of medical needs, said Tae Hyun Hwang, PhD, professor of Surgery, founding director of the Molecular AI Initiative, and director of AI Research for the Vanderbilt Section of Surgical Sciences. He noted that the 3D imaging could significantly advance development of therapeutic drugs, provide more detailed assessments of organ transplant rejections, assist with personalized medicine, and aid with tissue analysis for biopharmaceutical development. 

“This technology fundamentally redefines how we visualize and analyze tissue architecture, moving from traditional two-dimensional views to full 3D microenvironment mapping at the subcellular level,” said Hwang, a corresponding author of the study, who provided senior leadership in the development, validation and translational development of the technology. 

The 3D study published in Nature Communications introduced an innovative framework that integrates holotomography with deep learning to generate hematoxylin- and eosin-stained images directly from thick tissue samples. This noninvasive, AI-driven approach preserves tissue integrity, overcomes the traditional 4- to 5-micron thickness limit of routine histology, and enables volumetric visualization of biological structures up to 50 microns thick. 

By preserving tissue samples and avoiding chemical alteration, this method also ensures compatibility with downstream molecular assays, such as spatial transcriptomics, proteomics and genomic profiling — enhancing the breadth and depth of diagnostic and research capabilities.  

“This is not just a digital copy of hematoxylin- and eosin-staining,” Hwang said. “It is a foundational platform for AI-driven volumetric tissue analysis that accelerates discoveries in oncology, immunology, regenerative medicine and therapeutic development.” 

The multi-institutional effort also included researchers from KAIST, Tomocube Inc., Yonsei University College of Medicine and Mayo Clinic. Hwang received funding support from the National Cancer Institute (grants R01CA276690, R37CA265967, U01CA294518). 

VUMC researchers developed the MSI-SEER predictor technology in collaboration with Mayo Clinic, Yonsei Severance Hospital and Seoul St. Mary’s Hospital in South Korea. This technology identifies patients who will benefit from an immunotherapy that might otherwise be missed with existing prediction models. 

Microsatellite instability-high (MSI-H) status is a well-established biomarker used to identify patients likely to respond to immune checkpoint inhibitors, especially patients with gastrointestinal cancers. However, traditional testing methods — including immunohistochemistry and PCR-based assays — offer only a binary result and often miss focal or heterogeneous MSI-H regions within tumors.  

MSI-SEER overcomes this limitation by dividing each pathology slide into thousands of image tiles and generating region-by-region predictions of MSI-H probability. This enables visualization of the tumor’s spatial heterogeneity and quantification of the MSI-H fraction across the tumor. In multiple cases, MSI-SEER identified MSI-H regions in tumors previously classified as microsatellite stability, and those patients subsequently responded to immunotherapy. 

“This is analogous to what we say in HER2-low gastric cancer, where patients previously not eligible for targeted therapy are now being treated with agents like trastuzumab deruxtecan,” Hwang said. “Likewise, patients with low or heterogeneous MSI-features may now be reconsidered for immunotherapy if spatially resolved analysis like MSI-SEER is used.” 

A key innovation of MSI-SEER is its ability to report not only predictions but the confidence level for each result.  

“AI should not dictate clinical decisions; it should support them,” Hwang said. “MSI-SEER gives clinicians both the answer and a measure of how reliable the answer is. It’s not about replacing human expertise but about combining the best of AI computation with physician judgment to drive safe, precise decisions.” 

Hwang, who conceptualized the study and is the paper’s senior author, received research support from the National Cancer Institute and the Department of Defense. He also received support from the Eric and Wendy Schmidt Fund for AI Research and Innovation and the American Association for Cancer Research Innovation and Discovery Grant.  

Other VUMC researchers who authored the study are Sunho Park, PhD, Minji Kim, MS, Jean Clemenceau, PhD, and Inyeop Jang, PhD. 

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Experts on the research, clinical use, governance and ethical use of artificial intelligence gathered for the recent Vanderbilt-Ingram Cancer Center 26^th Annual Scientific Symposium. 

In a twist from years past, graduate students and postdoctoral fellows took the helm in selecting the topics and inviting speakers focused on “Artificial Intelligence in Cancer Research and Clinical Care.”

The keynote speakers were Eytan Ruppin, MD, PhD, chief of the Cancer Data Science Laboratory at the National Cancer Institute, and Gelareh Zadeh, MD, PhD, chair of the Department of Neurologic Surgery at Mayo Clinic.  

Ruppin detailed how he is developing computational approaches for advancing precision oncology, and Zadeh explained how she is using integrated multi-platform molecular analysis of brain tumors to predict patients’ responses to targeted therapies. Ruppin participated in panel discussions about artificial intelligence. 

“I am enriched talking to you guys,” Ruppin said. “I develop AI materials, but I am not using them to treat patients. I am learning a lot.” 

Douglas Flora, MD, executive medical director of Oncology Services at the Yung Family Cancer Center at St. Elizabeth in Edgewood, Kentucky, and the editor-in-chief of AI in Precision Oncology, replied, “All of us are cross pollinating. That’s why I love a symposium like this.” 

In opening the first panel discussion that focused on ethics, Ellen Wright Clayton, MD, JD, the Craig-Weaver Professor of Pediatrics, professor of Law and professor of Health Policy at Vanderbilt, framed artificial intelligence from an historical perspective, noting that “decision support is not new to medicine.” She gave specific examples of how clinicians can use artificial intelligence for decision support but stressed that they should not rely solely on it for treatment plans. 

“It is not OK simply to get the AI output and just do what it says,” Clayton said. “Maybe it is OK, but it is always required to see if that’s the right advice. Always.” 

In another twist from years past, the Mission Moment, which is a personal testament from a patient, was presented by a pediatric cancer survivor for the first time. Easton Reeder, 13, who has undergone surgery and chemotherapy for pilocytic astrocytoma — a type of brain tumor — shared about his experiences living with cancer. He told his story vividly with flashes of humor, describing how being tossed in the air like a rodeo clown by a Great Dane led to his diagnosis.

Clinicians initially concluded that he had a concussion because of persistent headaches that followed, but his mother, who is a nurse, insisted on a brain scan. Reeder, a committed athlete, who continued playing sports even while undergoing chemotherapy, was given a jersey signed by Vanderbilt baseball players.

“I learned that tomorrow isn’t a promise, and I have to make the best of every moment I have,” Reeder said. “I also learned that there is no ‘normal button.’ I have been trying to learn that power since forever, until I realized that power is not to be . . . God has proven to me that anything is possible through him.” 

In his welcoming remarks, Vanderbilt-Ingram director Ben Ho Park, MD, PhD, emphasized the importance of training new generations of cancer researchers and clinicians. 

“This is an opportunity for us to celebrate all the cancer research going on at Vanderbilt-Ingram,” Park said. “For all of you who don’t know, we really run the spectrum of everything research: clinical, population science, laboratory science and everything in between. This is our time of the year when we get to showcase and highlight not only the great science that our external panelists and presenters are going to bring — but you will be duly impressed, as I always am, by what our trainees bring to the table. The future really is bright, and we have to keep sustaining our future by encouraging and mentoring the next generation, which will ultimately lead to more cures.” 

Two tied in voting for the Graduate Student of the Year. Candace Grisham, MS, received the honor for her research into brain tumors, including a study she authored that was published in Clinical Neurology and Neurosurgery. Xiaopeng Sun, PhD, is the other co-awardee for his research into biomarkers to predict immunotherapy outcomes in patients, and his prolific contributions to that field of study, including 12 studies published in scientific journals. 

Guochong “Damon” Jia, PhD, MPH, is the Postdoctoral Scholar of the Year. He was selected for his high-impact research that has advanced the understanding of cancer genetics and epidemiology, including the largest genetic study ever conducted on breast cancer in African ancestry populations, which was published in Nature Genetics. 

The poster exhibition was one of the largest ever for the annual event. Sarah Reed took home the overall winner award for her entry “Identifying Genotype-Specific Effects of CHIP on Solid Tumors Using Chimeric Mouse Modeling and Clinical Data.” 

In the Translational Science Category, Julia Steele won first place; Alexander Kwiatkowski, PhD, won second place; Heather Beasley, PhD, won third place; and honorable mention went to Jacey Marshall. 

Robust participation in the Basic Science Category resulted in duplicate prizes due to the number of entries. Rachel Sinard and Lincoln Brown won first place prizes. Emily Green and Logan Vlach received second place awards, andAnna Gilbert and Alyssa Jarabek received third place awards. Honorable mentions went to Sydney Bates, Nicholas Eleuteri, Sarah Glass, PhD, Gabriela Gonzalez Vasquez, Maxwell Hamilton, Yash Pershad, Jared Rhodes and Brenda Rios. 

In the Population Science Category, Michael Betti received first place; Duc Huy Le, MD, MBA, received second place; and there was a tie for third place with Melissa Goldin and Jiajun Shi, PhD, both receiving awards. Honorable mention went to Grace Xu. 

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