ROCHESTER, Minn. — One of the most detailed maps to date of meningioma — the most common brain tumor in adults — reveals how the tumor's surrounding environment helps drive disease behavior and patient outcomes, according to new research from Mayo Clinic.

The study, published in Nature Genetics and conducted in collaboration with scientists at Princess Margaret Cancer Centre in Toronto, combines several advanced laboratory techniques to examine tumors at an unprecedented level of detail, offering clues to why some meningiomas grow slowly while others recur or become more aggressive. The findings could lead to more precise ways to predict risk and guide treatment decisions.

Growing evidence suggests that traditional grading systems for meningioma do not fully capture the behavior of these complex tumors, prompting the development of molecular classification tools that more accurately predict which tumors are more likely to recur after surgery. These new findings build on recent developments by investigating the signal from individual cells rather than whole tumors, demonstrating that the tumor microenvironment — the mix of immune and support cells surrounding the tumor — plays a critical role in shaping outcomes.

"We're seeing that it's not just the tumor cells themselves but the ecosystem around them that influences how these tumors grow and respond to treatment," says Gelareh Zadeh, M.D., Ph.D., a Mayo Clinic neurosurgeon and senior author of the study.

Understanding tumor behavior

An estimated 30,000 to 40,000 people in the U.S. are diagnosed with meningioma each year. While many tumors are benign, others can recur or become life-threatening, and predicting that risk has remained a major challenge.

In this study, researchers analyzed hundreds of tumor samples using techniques that allow them to study individual cells rather than averaging signals across the entire tumor. Using single-cell sequencing and spatial transcriptomics, the team mapped more than 500,000 individual cells and millions of data points across tumors. This created a high-resolution "atlas" of the genetic footprint of individual cells and how they differ between aggressive and benign tumors, how they change and evolve over space, and how they interact with other cells in their environment.

"Instead of looking at the tumor as a whole, we can now break it down into its individual components and understand what is driving its behavior," says Dr. Zadeh.

The researchers identified multiple distinct states of immune cells, particularly myeloid cells, that behave differently depending on the tumor. Some of these cell states were linked to more aggressive disease, while others were associated with better outcomes.

Implications for patient care

The findings build on earlier work from Mayo Clinic researchers outlining a new era of personalized care for meningioma, where molecular and cellular insights guide clinical decision-making. This latest study adds a critical layer by showing how the tumor microenvironment contributes to that personalization.

Researchers found that certain immune cell programs were strongly linked to how quickly tumors returned after treatment. In some cases, these signals were able to add value to tumor grade and even modern molecular classification systems in their ability to predict patient outcomes, suggesting they could help refine decisions about surgery, radiation or closer follow-up in the future.

The study also showed that these biological signatures may be detectable through noninvasive approaches, such as blood-based biomarkers, raising the possibility of monitoring patients over time without repeated surgery.

"This moves us closer to a future where we can better stratify patients — identifying who needs more aggressive therapy and who may avoid overtreatment," says Dr. Zadeh.

Beyond improving prognostic tools, the research highlights potential therapeutic targets. By identifying how immune cells and tumor cells communicate, the study points to pathways that could be disrupted to slow tumor growth or enhance treatment response.

Next steps include validating the findings in larger, multicenter cohorts and translating these biological insights into clinical tools and prospective trials.

For a complete list of authors, disclosures and funding, review the study. 

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About Mayo Clinic
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news. 

Media contact:

• Tia Ford, Mayo Clinic Communications, newsbureau@mayo.edu

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ROCHESTER, Minn. — Mayo Clinic researchers and collaborators have shown that an artificial intelligence (AI) tool can analyze routine pathology slides to help clinicians classify meningiomas, the most common primary brain tumor in adults, and better understand a patient’s risk of tumor recurrence.

The study, published in The Lancet Digital Health, demonstrates that deep learning models can support the extraction of molecular and prognostic information from standard hematoxylin and eosin, or H&E, slides — the same type of tissue images already used in routine clinical care. These insights are typically obtained through DNA methylation profiling, an advanced genetic test which provides valuable diagnostic and prognostic information but can be costly, time-consuming and is unavailable in many hospitals.

"This is one of the many studies where we can harness the strength of digital pathology by capturing the last two decades of genomic and molecular knowledge into AI algorithms," says Gelareh Zadeh, M.D., Ph.D., chair of the Department of Neurologic Surgery at Mayo Clinic in Rochester and the David C. and Flora C. Pratt Distinguished Chief Medical Officer for Mayo Clinic Platform.

Making advanced tumor insights more accessible

Meningiomas can vary widely in behavior. Some grow slowly and may never return after treatment, while others are more aggressive and more likely to recur. Understanding that risk is critical for patients and care teams deciding whether additional treatment, such as radiation therapy, may be needed after surgery.

Molecular testing can help identify which tumors are more likely to recur and which may respond differently to treatment. But these tests require specialized technology and expertise, limiting access for many patients.

Using tissue samples, pathology images and clinical data from 672 patients, researchers developed and tested AI models designed to help identify patterns linked to a tumor's biology. Drawing on multiple de-identified datasets, including data resources from Mayo Clinic Platform, the models supported classification of meningioma subtypes and recurrence risk prediction using standard pathology slides that are already part of routine patient care.

The findings suggest that, with further validation, AI-based tools could one day help clinicians obtain more detailed tumor information to inform patient care, without requiring every patient to undergo advanced genetic testing.

Helping guide treatment decisions

For patients with meningiomas, recurrence risk can influence follow-up care, imaging frequency and whether radiation therapy should be considered. The study found that AI-based predictions remained useful even after accounting for traditional clinical factors such as tumor grade, the extent to which surgery was able to remove the tumor and patient age.

Researchers also found that the AI models could identify patterns of tumor heterogeneity — differences within the same tumor — that may help explain why some tumors behave more aggressively or respond differently to treatment.

The researchers note that additional prospective studies are needed before the AI models can be used routinely in clinical care. Still, they say the findings lay the groundwork for more accessible, personalized care for patients with meningiomas — and potentially for similar AI approaches in other cancers.

As with any clinical decision-support tool, the researchers emphasize that these models would require rigorous evaluation, validation and ongoing physician oversight before being considered for routine care. "The aim is to make these algorithms readily and simply accessible for use globally, improving patient care across many healthcare settings," says Dr. Zadeh.

For a complete list of authors, disclosures and funding, review the publication.

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About Mayo Clinic
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.

About Mayo Clinic Platform
Founded on Mayo Clinic's dedication to patient-centered care, Mayo Clinic Platform enables new knowledge, new solutions, and new technologies through collaborations with health technology innovators to create a healthier world. To learn more, visit Mayo Clinic Platform at www.mayoclinicplatform.org.

Media contact:

• Tia Ford, Mayo Clinic Communications, newsbureau@mayo.edu

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PHOENIX — An experimental drug combination may help overcome treatment resistance in advanced kidney cancer, according to early results from a first-in-human clinical trial led by Mayo Clinic researchers.

The study evaluated the investigational drug darlifarnib in combination with the targeted therapy cabozantinib, a standard treatment for clear cell renal cell carcinoma (ccRCC), the most common type of kidney cancer. Among patients whose disease had progressed despite prior treatment, 44% responded to the combination therapy, while disease control was achieved in 94% of participants.

"These early findings are encouraging, as more effective treatments are urgently needed for patients with advanced disease," says Yousef Zakharia, M.D., principal investigator of the study and a medical oncologist at Mayo Clinic in Arizona. He presented the findings at the 2026 International Kidney Cancer Symposium: Europe in Paris.

ccRCC accounts for most kidney cancer cases in adults, and many patients eventually experience disease progression despite treatment.

In the phase 1a/b study, researchers evaluated 18 patients who had previously received cabozantinib. About half had undergone at least three prior therapies.

"For many patients, the benefit of cabozantinib can be temporary. Tumors may develop resistance and activate alternative pathways that allow the cancer to continue growing," Dr. Zakharia says.

Researchers investigated whether adding darlifarnib, a next-generation targeted therapy designed to inhibit cancer growth signaling pathways, could help overcome treatment resistance.

The combination produced tumor shrinkage in 7 of 16 evaluable patients, corresponding to an overall response rate of 44%. Disease control, defined as either tumor stability or shrinkage, was achieved in 15 of 16 patients (94%).

"These findings require validation in a larger clinical trial to confirm the efficacy observed thus far; however, the early signal is intriguing," says Dr. Zakharia. "This study represents an important step forward and provides insight into how treatment resistance might be overcome."

The multicenter, international trial will further evaluate the benefit of the combination in a larger group.

For a complete list of trial and funding information, review the study.

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About Mayo Clinic
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.

About Mayo Clinic Comprehensive Cancer Center
Designated as a comprehensive cancer center by the National Cancer Institute, Mayo Clinic Comprehensive Cancer Center is defining the cancer center of the future, focused on delivering the world's most exceptional patient-centered cancer care for everyone. At Mayo Clinic Comprehensive Cancer Center, a culture of innovation and collaboration is driving research breakthroughs in cancer detection, prevention and treatment to change lives.

Media contact:

• Julie Ferris-Tilman, Ph.D., Mayo Clinic Communications, newsbureau@mayo.edu

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ROCHESTER, Minn. — Mayo Clinic Comprehensive Cancer Center researchers will present more than 30 studies at the 2026 American Society of Clinical Oncology (ASCO) Annual Meeting, highlighting advances in precision oncology, early cancer detection, artificial intelligence (AI) and personalized cancer care. The meeting will be held May 29–June 2 at the McCormick Place Convention Center in Chicago.

Featured research includes biomarker-driven treatments for bladder and lung cancers, new approaches for triple-negative breast cancer, multicancer early detection testing, and AI-enabled analysis of the tumor microenvironment in colon cancer.

Highlighted presentations include:

Education Session: Triple-Negative Breast Cancer in 2026: Translating New Data into Clinical Decisions
Presentation time: May 30, 4:45–5 p.m. CDT
Presentation title: Stage 1 Triple-Negative Breast Cancer: Who Needs What Treatment?
Presenter: Roberto Leon-Ferre, M.D., associate professor of oncology

Poster Session: Gastrointestinal Cancer — Colorectal and Anal
Presentation time: May 30, 9 a.m.–Noon CDT
Presentation title: Health-related quality of life (HRQOL) in the phase 3 trial of standard chemotherapy alone or combined with atezolizumab as adjuvant therapy for patients with stage 3 deficient DNA mismatch repair (dMMR) colon cancer (Alliance A021502, ATOMIC) (Abstract 2636)
Presenter: Amylou Dueck, Ph.D., professor of biostatistics

Poster Session: Gastrointestinal Cancer — Colorectal and Anal
Presentation time: May 30, 9 a.m.–Noon CDT
Presentation title: A deep learning approach to quantify tumor microenvironment features associated with postoperative ctDNA status and outcomes in a phase 3 FOLFOX-based adjuvant colon cancer trial (N0147; Alliance) (Abstract 3525)
Presenter: Frank Sinicrope, M.D., professor of medicine and oncology

Poster Session: Care Delivery/Models of Care
Presentation time: May 30, 9 a.m.–Noon CDT
Presentation title: Fertility concerns, counseling and preservation in AYA females with early-stage breast cancer: Chemotherapy receipt and timing (Abstract 1564)
Presenter: Bolun Liu, M.D., assistant professor of medicine

Education Session: It's 2026: Updates in Small Cell Lung Cancer — No Longer Too Small to Ignore
Presentation time: May 31, 8–8:15 a.m. CDT
Presentation title: Systemic Therapy for Small Cell Lung Cancer: Standard of Care and Recent Therapeutic Advances
Presenter: Rami Manochakian, M.D., associate professor of medicine

Case-Based Panel Session: Biomarker Treatment Strategies for Bladder Cancer: Putting the Patient at the Center
Presentation time: May 31, 8–9 a.m. CDT
Presentation title: Surgical Oncologist Perspective
Presenter: Mark Tyson II, M.D., professor of urology

Oral Abstract Session: Prevention, Risk Reduction and Genetics
Presentation time: May 31, 9:45–9:51 a.m. CDT
Presentation title: Safety and performance results from PATHFINDER 2, a registrational study of a multicancer early detection (MCED) test in an intended-use population (Abstract LBA10509)
Presenter: Karthik Giridhar, M.D., assistant professor of oncology

Poster Session: Gynecologic Cancer
Presentation time: June 1, 9 a.m.–Noon CDT
Presentation title: Development of an endometrial cancer test from a vaginal swab (Abstract 5624)
Presenter: Jamie Bakkum-Gamez, M.D., professor of obstetrics and gynecology

Poster Session: Breast Cancer — Local/Regional/Adjuvant
Presentation time: June 1, 1:30–4:30 p.m. CDT
Presentation title: A randomized phase 2 trial of folate receptor alpha peptide vaccine in early-stage triple-negative breast cancer (Abstract 536)
Presenter: Kathryn Ruddy, M.D., professor of oncology, Keith Knutson, Ph.D., professor of immunology, and co-author Saranya Chumsri, M.D., professor of oncology

Poster Session: Breast Cancer — Metastatic
Presentation time: June 1, 1:30–4:30 p.m. CDT
Presentation title: Quality of life and treatment tolerability of Bria-IMT + CPI in metastatic breast cancer (Abstract 1107)
Presenter: Saranya Chumsri, M.D., professor of oncology

Oral Abstract Session: Hematologic Malignancies — Leukemia, Myelodysplastic Syndromes, and Allotransplant
Presentation time: June 2, 9:57–10:09 a.m. CDT
Presentation title: RALLY-MF: Initial efficacy of a phase 2 study of DISC-0974, an anti-hemojuvelin antibody, to treat anemia in myelofibrosis (Abstract 6501)
Presenter: Naseema Gangat, M.B.B.S., professor of medicine and co-author Ayalew Tefferi, M.D., professor of medicine and Barbara Woodward Lips Professor II

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About Mayo Clinic
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.

About Mayo Clinic Comprehensive Cancer Center
Designated as a comprehensive cancer center by the National Cancer Institute, Mayo Clinic Comprehensive Cancer Center is defining the cancer center of the future, focused on delivering the world's most exceptional patient-centered cancer care for everyone. At Mayo Clinic Comprehensive Cancer Center, a culture of innovation and collaboration is driving research breakthroughs in cancer detection, prevention and treatment to change lives.

Media contact:

• Julie Ferris-Tillman, Ph.D., Mayo Clinic Communications, newsbureau@mayo.edu

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A new era of medicine is emerging at Mayo Clinic — one that finds disease before symptoms appear 

ROCHESTER, Minn. — When Mayo Clinic researchers sequenced the genomes of 484 seemingly healthy adults, they found that about 13% carried a serious, previously unrecognized genomic risk — conditions those patients did not know about and that standard care would likely miss.

Nearly all participants, 98.6%, had at least one genetic finding, and for most, the results called for monitoring. The study, published in Genetics in Medicine, also takes a closer look at what it takes to turn those findings into the proper follow-up care.

Among the 13%, the actionable findings pointed to serious risks, including hereditary breast and ovarian cancer; Lynch syndrome, linked to colorectal cancer; cardiomyopathy; long QT syndrome; and amyloidosis.

"These are people traditional testing based on symptoms or family history would not identify," says Dr. Konstantinos Lazaridis, the Carlson and Nelson Endowed Executive Director of the Center for Individualized Medicine and senior author of the study. "This study helps define the blueprint for integrating genomic insight into care at scale — turning information into decisions that can change the trajectory of disease."

From discovery to care

Identifying the risk, it turns out, is the easiest part. Acting on it is far more complex. Nearly every case required clinical interpretation, documentation and communication. This work fell largely to genetic counselors, who reviewed results, prepared individualized summaries and helped guide next steps for patients and care teams.

"Genetic counselors are often the first people to share this kind of information with patients," says Jessa Bidwell, a certified research genetic counselor and first author of the study. "There can be surprise, anxiety, devastation, and at times relief at finally having an explanation. Our role is to meet people in that moment and help them understand what their health risks might be, based on the genetic finding, and their personal and family history."

Most participants with actionable findings followed through, completing referrals and connecting with primary care specialists. Yet fewer than half had a documented conversation with a primary care professional after receiving results — underscoring how difficult it remains to integrate genomic findings into routine care.

The study positions predictive genomic screening as both a clinical opportunity and a systems challenge. The science exists. Researchers and clinicians are still building the infrastructure to act on it consistently.

At Mayo Clinic, that infrastructure is beginning to take shape through an initiative called Precure. Genomic screening is one part of that initiative, which aims to detect disease earlier by combining genetic data with other biological signals.

"Precure is one example of a moonshot for human health at Mayo Clinic," says Dr. Lazaridis, who leads the initiative. "It reflects Mayo Clinic's commitment to move medicine beyond treatment and toward lasting wellness." - Dr. Lazaridis

Predicting disease before it begins 

Most diseases don't arrive without warning. They begin with small shifts in genes, molecules, proteins and immune signals that develop over time, often years before symptoms appear.

Precure is Mayo Clinic's enterprise-wide effort to detect those early signals and intervene sooner. Powered by advanced computing and artificial intelligence (AI), the initiative currently focuses on five organ systems — the brain, heart, kidneys, liver and lungs — studying conditions such as Alzheimer's disease, heart failure and chronic liver disease to better understand how they emerge and progress.

The work draws on expertise from across Mayo Clinic and is supported by Mayo Clinic Platform, which brings together large-scale patient data and advanced computing to enable scientists to study disease across populations.

"Precure is one example of a moonshot for human health at Mayo Clinic," says Dr. Lazaridis, who leads the initiative. "It reflects Mayo Clinic's commitment to move medicine beyond treatment and toward lasting wellness."

Precure is part of Mayo Clinic's Bold. Forward. strategy to Cure, Connect and Transform healthcare. The genomic screening study is an early demonstration of what that looks like in practice: science that doesn't wait for disease to announce itself, and a system already being built to act on what it finds.

For a complete list of authors, disclosures and funding information, review the study. 

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About Mayo Clinic
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.

Media contact:

• Julie Ferris-Tillman, Ph.D., Mayo Clinic Communications, newsbureau@mayo.edu

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ROCHESTER, Minn. — Mayo Clinic and Stanford Medicine researchers have developed the first blood test to map the complex ecosystem surrounding cancer cells, offering a more accurate way to predict which patients will benefit from immunotherapy. Their study's findings, published in Nature, represent a major advance in precision oncology and could help guide treatment decisions across multiple cancer types and treatments.

"This is a complete paradigm shift," says Aadel Chaudhuri, M.D., Ph.D., professor of radiation oncology at Mayo Clinic and co-senior author of the study. "Until now, liquid biopsies or blood tests have focused almost entirely on tumor cells. For the first time, we can use a simple blood test to understand the tumor's microenvironment, which is critical for determining how patients respond to modern cancer therapies."

Capturing and mapping the tumor environment

Immunotherapy has transformed cancer care, but only for some patients. Current tools used to predict tumor response, such as testing for the number of DNA mutations in a tumor and the levels of certain proteins on a cancer cell, aren't able to capture the level of detail needed.  

"One of the challenges is that these existing methods only have modest associations," Dr. Chaudhuri says. "They're essentially 'surrogates of surrogates' and don't fully capture what's happening inside the tumor environment."

To address this gap, the research team posed the question: Can a better readout of the tumor microenvironment be developed from a liquid biopsy of a patient's blood?

To start their investigation, they turned to spatial transcriptomics, an advanced technique that maps how different cells interact within a tumor. By analyzing tumor samples, they identified nine distinct cellular neighborhoods, or spatial ecotypes, each representing a unique immune and stromal (the noncancerous cells and structures surrounding the tumor) environment.

"Almost like geographic mapping, we were able to map where in the tumor microenvironment these neighborhoods of co-associated cells live," Dr. Chaudhuri explains. All 17 tested cancer types share these neighborhoods; some are more likely to occur at the border of the tumor and healthy tissue, while others were more likely found deeper inside the tumor. "Then, we showed that certain neighborhoods, or spatial ecotypes, are associated with survival and immunotherapy response outcomes."

Using AI to develop a simple blood test

To identify these tumor neighborhoods, the team collaborated with Aaron Newman, Ph.D., associate professor of biomedical data science at Stanford Medicine and co-senior author of the study. Newman's team developed methods to define these neighborhoods from tumor samples and an artificial intelligence (AI) framework to detect them in blood.

Using methylation — chemical markings on DNA that help control gene activity — on cell-free DNA shed by tumors into the bloodstream, the researchers created a liquid biopsy test that details the tumor microenvironment beyond its cancer cells. This means a blood draw, not an incision, is all it takes to profile the tumor's spatial ecotypes.

"This is the first time we've been able to noninvasively profile the tumor microenvironment at this level," says Dr. Chaudhuri.

In studies involving more than 1,300 patients across multiple cancers, including melanoma, lung, bladder and gastric cancers, specific spatial ecotypes were strongly associated with treatment outcomes. Certain ecotypes are predicted to respond positively to immunotherapy, while others were linked to treatment resistance and poorer survival. Standard biomarkers showed inferior predictive power.

Improving treatment decisions and avoiding side effects

The ability to predict immunotherapy response before starting treatment could have an immediate clinical impact.

Cancer therapy can be time-consuming and carry significant side effects. Identifying patients unlikely to benefit from immunotherapy could allow clinicians to choose more effective alternate therapies sooner.

"If a patient isn't going to respond, that's time we could be using a different treatment," Dr. Chaudhuri says. "Better upfront decision-making can directly improve outcomes."

Importantly, finding likely resistance to an immunotherapy is not necessarily bad news. It may help guide patients toward different treatments better suited to their tumor biology, further guided by the patient's personalized spatial ecotype profile.

Tracking cancer progress in real time

Because the test is blood-based, it also opens the door to ongoing monitoring of how a patient's tumor microenvironment evolves during treatment.

In early data, researchers observed that changes in spatial ecotypes could signal treatment response or resistance months before traditional imaging can.

"This gives us a window into how the tumor microenvironment is changing over time," says Dr. Chaudhuri. "We've never been able to see that before in a practical way."

Broadening the approach across cancers and other diseases

While the initial study focused primarily on patients with melanoma, the approach shows promise across many cancers, including lung cancer and bladder cancer, where treatment decisions are complex and time sensitive. The research team has new data beyond the published study showing the ability to predict complete responses to antibody drug conjugate (ADC)-based combination therapy. Researchers also believe the technology-assisted approach could eventually extend beyond cancer testing and treatment.

"This is not just about cancer," Dr. Chaudhuri says. "It could provide insights into a wide range of diseases by helping us understand complex biological environments in the body."

Further studies are underway to validate the test in larger patient populations and move it into clinical use. Researchers are also exploring how different tumor microenvironment patterns may predict response to other therapies beyond immunotherapy.

"This work opens up an entirely new way of thinking about disease," Dr. Chaudhuri says. "We've essentially uncovered a world that was invisible to us before — and now we can access it with a simple blood test."

Aadel Chaudhuri, M.D., Ph.D., has patent filings related to liquid biopsy and cancer biomarkers, and has ownership interests in Droplet Biosciences and LiquidCell Dx. Aaron Newman, Ph.D., has patent filings related to digital cytometry, liquid biopsy and cancer biomarkers. He has served as a consultant to, and has ownership interests in, CiberMed and LiquidCell Dx.

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About Mayo Clinic
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.

Media contact:

• Julie Ferris-Tillman, Ph.D., Mayo Clinic Communications, newsbureau@mayo.edu

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ROCHESTER, Minn. — Research from Mayo Clinic is helping refine how multiple myeloma is diagnosed and treated, with findings that support more personalized therapies and identify promising immunotherapy strategies for aggressive forms of the disease.

The research led by Sikander Ailawadhi, M.D., Shaji Kumar, M.D., Akhilesh Pandey, M.D., Ph.D., and Richard Kandasamy, Ph.D. in the Mayo Clinic Comprehensive Cancer Center, focuses on tailoring treatment based on disease biology and improving outcomes for patients living longer with the cancer.

Treating multiple myeloma as a chronic disease

Multiple myeloma, a blood cancer that affects plasma cells in the bone marrow, can cause abnormal proteins to accumulate and damage organs. At Mayo Clinic, patients with multiple myeloma receive tailored treatment that varies from person to person based on how the disease develops and progresses.

Care strategies continue to evolve, including immunotherapy and clinical trials that study the most effective order to use available treatments. One approach uses monoclonal antibodies given in sequence to better target cancer cells and improve outcomes for patients whose disease has returned.

"We take into account the risks, but also what the patients' wants, needs and aspirations are, and make a decision about treatment that brings all this together," says Dr. Ailawadhi, a hematologist and oncologist. "Much has been learned about the best use of novel treatments such as CAR-T and other immunotherapy approaches."

New immunotherapy strategies show promise

In one area of research, Dr. Kumar, a hematologist, and colleagues published a study in the New England Journal of Medicine showing that an off-the-shelf dual-antibody immunotherapy can produce deep and durable responses in extramedullary multiple myeloma, a form of the disease with historically limited treatment options.

"We are seeing powerful responses in a disease that historically has resisted every therapy," says Dr. Kumar.

The approach uses two engineered antibodies to engage T cells through separate immune pathways, directing an immune response against myeloma cells. The treatment is administered in a standard infusion setting, in contrast to more complex cell therapies.

In early results, a majority of patients responded to the treatment, and many achieved no detectable disease, suggesting a potential new option for patients with resistant disease.

Seeing what standard tests miss

Understanding the full genetic profile of multiple myeloma remains a key challenge in care.

Dr. Pandey, a clinical pathologist in Laboratory Medicine and Pathology, and Dr. Kandasamy, a systems biologist, are collaborating with other researchers to study a potential new approach to defining the disease. Multiple myeloma is driven by changes in chromosomes that affect prognosis and treatment decisions. Standard testing uses fluorescence in situ hybridization, or FISH, which looks for specific known changes but may not capture the full picture.

A newer method, Genomic Proximity Mapping (GPM), analyzes a patient's entire genome. It can identify structural changes, gains or losses of genetic material and complex rearrangements, including high-risk features. In early studies, GPM confirmed results from standard testing and identified additional clinically important changes.

"This approach could improve risk assessment and help doctors choose treatments that are better tailored to each individual," says Dr. Pandey.

Researchers are now studying GPM testing in larger patient groups and exploring its use in other cancers.

“Beyond multiple myeloma, GPM can identify complex and hidden genetic changes. This means it could be useful across many types of cancer and help give a clearer picture of each person’s disease,” says Dr. Kandasamy.

Looking ahead toward precision care

As multiple myeloma care continues to evolve, new therapies will expand options for resistant disease and advances in testing will help guide treatment decisions. Comprehensive tools such as Genomic Proximity Mapping (GPM) may further refine risk assessment and support earlier, more precise care for patients.

Other clinical trials are evaluating the benefits of earlier use of immunotherapies in treatment and improved supportive care.

While multiple myeloma is considered treatable but not curable, these developments may help extend survival and improve quality of life, with a growing subset of patients achieving long-term remission.

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About Mayo Clinic
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.

Media contact:

• Julie Ferris-Tillman, Ph.D., Mayo Clinic Communications, newsbureau@mayo.edu

The post Improving how multiple myeloma is understood and treated appeared first on Mayo Clinic News Network.

ROCHESTER, Minn. — A Mayo Clinic-developed artificial intelligence (AI) model can help specialists detect pancreatic cancer on routine abdominal CT scans up to three years before clinical diagnosis. It identifies subtle signs of disease before tumors are visible, when curative treatment may still be possible. The findings, published in Gut, mark a milestone in Mayo Clinic's multiyear research effort to enable earlier detection of one of the deadliest cancers.

The study validates this next-generation AI model using data and workflows that mirror clinical practice, including CT scans from multiple institutions, imaging systems and protocols.

Researchers used the AI model to analyze nearly 2,000 CT scans, including scans from patients later diagnosed with pancreatic cancer — all originally interpreted as normal. The system, called the Radiomics-based Early Detection Model (REDMOD), identified 73% of those prediagnostic cancers at a median of about 16 months before diagnosis — nearly double the detection rate of specialists reviewing the same scans without AI assistance.

The advantage was even greater at earlier time points. In scans obtained more than two years before diagnosis, the AI identified nearly three times as many early cancers that would otherwise go undetected.

Pancreatic cancer remains one of the deadliest cancers because it rarely causes detectable signs in its earliest stages. More than 85% of patients receive a diagnosis after the disease has already spread, and five-year survival rates remain below 15%, according to the National Cancer Institute. Projections show it will become the second-leading cause of cancer-related death in the U.S. by 2030.

"The greatest barrier to saving lives from pancreatic cancer has been our inability to see the disease when it is still curable," says Ajit Goenka, M.D., the study's senior author, and a Mayo Clinic radiologist and nuclear medicine specialist. "This AI can now identify the signature of cancer from a normal-appearing pancreas, and it can do so reliably over time and across diverse clinical settings." 

REDMOD measures hundreds of quantitative imaging features that describe tissue texture and structure, capturing faint biological changes as cancer begins to develop. The model is designed to analyze CT scans already obtained for other reasons — particularly in high-risk patients, such as those with new-onset diabetes — and flag elevated risk before any visible mass appears. 

The model runs automatically without time-intensive manual preparation. The team validated the model across CT scans from multiple institutions, imaging systems and protocols, demonstrating consistent performance beyond a single dataset.

The model's predictions also remained stable over time. In patients with multiple scans, the AI produced consistent results months apart, supporting its use for longitudinal monitoring and early detection. 

"This AI can now identify the signature of cancer from a normal-appearing pancreas, and it can do so reliably over time and across diverse clinical settings."  - Dr. Ajit Goenka

Researchers are advancing this work into clinical testing through Artificial Intelligence for Pancreatic Cancer Early Detection, or AI-PACED. This prospective study evaluates how clinicians can integrate AI-guided detection into care for patients at elevated risk. The study combines AI analysis of routine imaging with longitudinal follow-up to assess performance, including early detection, false positives and clinical outcomes. 

This research is part of Mayo Clinic's Precure initiative, which aims to predict and prevent disease by identifying the earliest biological changes in the body before symptoms begin. It also reflects Mayo Clinic's Clinical Impact strategy, accelerating the translation of discovery into patient care. 

The study was supported by the National Institutes of Health, the Hoveida Family Foundation, the Mayo Clinic Comprehensive Cancer Center and the Champions for Hope Pancreas Cancer Research Program of the Funk-Zitiello Foundation. 

For a complete list of authors, disclosures and funding, review the study. 

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About Mayo Clinic  
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.  

About Mayo Clinic Comprehensive Cancer Center  
Designated as a comprehensive cancer center by the National Cancer Institute, Mayo Clinic Comprehensive Cancer Center is defining the cancer center of the future, focused on delivering the world's most exceptional patient-centered cancer care for everyone. At Mayo Clinic Comprehensive Cancer Center, a culture of innovation and collaboration is driving research breakthroughs in cancer detection, prevention and treatment to change lives. 

Media contact:   

• Julie Ferris-Tillman, Ph.D., Mayo Clinic Communications, newsbureau@mayo.edu  

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ROCHESTER, Minn. — A comprehensive new review led by Mayo Clinic is helping shape how clinicians diagnose and treat meningioma, the most common primary brain tumor, with a focus on personalized, patient-centered care and the latest advances in precision oncology.

Published in Nature Reviews Clinical Oncology, the review brings together global expertise to map the future of meningioma care, highlighting innovations that aim to improve outcomes and quality of life for patients.

"This work synthesizes rapidly evolving science to support more personalized care for patients with meningioma," says Gelareh Zadeh, M.D., Ph.D., chair of the Department of Neurologic Surgery at Mayo Clinic in Rochester and senior author of the review. "With insights and technologies emerging quickly, there is an urgent need to translate new knowledge into clinical practice. This review helps care teams make more informed decisions to improve outcomes and quality of life for patients."

Putting patients first through precision medicine

Meningiomas account for about 37% of all central nervous system tumors and can significantly affect neurological function depending on their location.

Traditionally, treatment decisions have relied on tumor appearance under a microscope. The review highlights a major shift: integrating molecular, imaging and clinical data to tailor care for each patient. Key advances include:

• More accurate diagnosis and prognosis. New molecular classification systems are improving the ability to predict which tumors are likely to grow or recur, enabling earlier and more personalized care decisions.
• Earlier detection of recurrence. Advanced imaging, such as PET/MRI, helps clinicians better detect residual or returning tumors sooner, helping guide timely treatment.
• Less invasive, safer treatments. Innovations in surgical techniques and precision radiotherapy improve outcomes while reducing complications and preserving function.

A more personalized treatment pathway

The review outlines a modern, multidisciplinary approach to meningioma care: one that adapts to each patient rather than relying on a generalized approach. For some patients, that may mean active surveillance to avoid unnecessary treatment and preserve quality of life. For others, advances in minimally invasive surgery and highly targeted radiation therapy are making treatment safer and more precise.

At the same time, new options are emerging for more complex cases. Targeted drugs, immunotherapy and radioligand therapies are expanding what's possible for patients with aggressive or recurrent tumors. These treatments are increasingly guided by molecular profiling and advanced imaging, helping care teams better understand each tumor and select the most effective approach.

Together, these advances are helping shift meningioma care toward more personalized, timely treatment to improve outcomes while reducing unnecessary interventions.

"This is about redefining how we care for patients with the most common type of brain tumor," says Dr. Zadeh. "It moves us beyond a one-size-fits-all approach toward more personalized care."

For a complete list of authors, disclosures and funding, review the publication.

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About Mayo Clinic
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.

Media contact:

• Tia Ford, Mayo Clinic Communications, newsbureau@mayo.edu

The post Mayo Clinic researchers outline a new era of personalized care for patients with meningioma appeared first on Mayo Clinic News Network.

ROCHESTER, Minn. — Mayo Clinic Comprehensive Cancer Center scientists, physicians and trainees will present nearly 60 studies on emerging cancer therapies, diagnostics and prevention strategies at the 2026 American Association for Cancer Research (AACR) Annual Meeting, April 17–22 at the San Diego Convention Center. The meeting is a premier forum for the global cancer research community to share the latest advances in cancer science and medicine.  

Mayo Clinic presentations will highlight advances in tumor biology, outcomes and risk prediction, as well as new treatment strategies and practice-changing studies in breast, colorectal, brain and prostate cancers.

Discoveries at the meeting include:

Poster Session: Immune Cell Biology and Tumor-Immune Crosstalk
Presentation time: April 19, 2–5 p.m. PDT
Poster title: Rewiring the dendritic cell: Regulatory T cell axis sensitizes prostate cancer to immunotherapy
Description: The study investigates whether increasing the number and functionality of dendritic cells simultaneously with Treg depletion is effective in overcoming the distinctly "cold" prostate tumor microenvironment. The findings have the potential to yield new immunotherapeutic approaches for prostate cancer treatment.
Presenter: Casey Ager, Ph.D., assistant professor of immunology

Poster Session: Biomarkers Predictive of Therapeutic Benefit 2
Presentation time: April 19, 2–5 p.m. PDT
Poster title: Blinded clinical validation of LiquidTME, a cell-free DNA assay for predicting response to immunotherapy by noninvasively profiling the tumor microenvironment
Description: Researchers show that using a practical liquid biopsy approach to profile the tumor microenvironment can predict immunotherapy response in melanoma patients.
Presenter: Aadel Chaudhuri, M.D., professor of radiation oncology

Poster Session: Molecular Imaging, Radiomics, and Theranostics
Presentation time: April 20, 9 a.m.–noon PDT
Poster title: Prospective evaluation of 68Ga-PSMA PET imaging in advanced hepatocellular carcinoma patients undergoing first-line immunotherapy 
Description: The study evaluated whether new imaging markers from a specialized scan (PSMA PET/CT) could help track how well patients with advanced liver cancer respond to their first immunotherapy treatment.
Presenter: Nguyen Tran, M.D., associate professor of oncology

Poster Session: CAR-T Cell Targets and TME Reprogramming
Presentation time: April 20, 9 a.m.–12 p.m. PDT
Poster title: Optimized CAR-T cell therapy to remodel the tumor microenvironment and eliminate GI malignancies
Description: Scientists developed a more precise chimeric antigen receptor T-cell therapy (CAR-T therapy) with a built-in "on switch" that can safely break through a protective barrier in solid tumors and attack the cancer. This strategy could offer a new and more effective way to treat advanced gastrointestinal cancers.
Presenter: Omar Gutierrez Ruiz, Ph.D., research fellow in hematology; Principal investigator: Saad Kenderian, M.B., Ch.B., associate professor of oncology

Oral Presentation Session: Biomarkers That Change Management: Predicting Therapy Benefit, Progression, and Metastatic Risk
Presentation time: April 20, 3:20–3:35 p.m. PDT
Presentation title: Stromal immune composition significantly contributes to adenomatous polyp recurrence or progression to cancer
Description: The study findings show that the environment surrounding colon polyps, including immune cells and supportive tissue, plays a role in why polyps can return after removal and develop into colorectal cancer. The findings could be key to developing more effective prevention strategies.
Presenter: Mrunal Dehankar, senior bioinformatician; Principal investigator: Lisa Boardman, M.D., professor of medicine

Poster Session: Biomarkers Predictive of Therapeutic Benefit 5
Presentation time: April 21, 9 a.m.–noon PDT
Poster title: Molecular correlates of progression-free survival in recurrent gliomas treated with pembrolizumab
Description: The study aimed to identify molecular predictors of progression-free survival (PFS) in recurrent glioma patients treated with pembrolizumab. The drug showed limited overall efficacy, but exploratory analyses identified several subtype-specific genomic alterations that may correlate with PFS. The findings highlight the potential influence of underlying tumor biology on immunotherapy response and warrant further validation in larger, prospective cohorts.
Presenter: Shameel Shafqat, M.B.B.S, visiting research fellow; Principal investigator: Sani Kizilbash, M.D., associate professor of oncology

Poster Session: Vaccines and Other Immunomodulatory Agents
Presentation time: April 21, 2–5 p.m. PDT
Poster title: Safety, tolerability, and early immune responses in the safety run-in of an HER2 multi-epitope vaccine combined with T-DM1 in residual HER2-positive breast cancer
Description: The first study to demonstrate that a cancer vaccine can be delivered concurrently with an antibody-drug conjugate without increasing adverse effects while still eliciting robust T-cell responses. 
Presenter: Saranya Chumsri, M.D., associate professor of medicine

Poster Session: Tumor Microenvironment, Multispecifics, and Immunomodulation
Presentation time: April 21, 2–5 p.m. PDT
Poster title: Combined KRAS pathway inhibition and liposomal irinotecan treatment enhances tumor regression, attenuates desmoplasia, and augments T cell infiltration in pancreatic ductal adenocarcinoma
Description: Researchers discovered a dual-drug combination that shrank tumors and helped break down the tumor's protective barrier, allowing the body's immune system to better attack the cancer. The approach improved survival in preclinical studies, pointing to a promising new treatment strategy for pancreatic cancer.
Presenter: Hari Krishnareddy Rachamala, Ph.D., assistant professor of biochemistry and molecular biology

Poster Session: Functional and Spatial Regulation of Immune Evasion and Anti-Tumor Immunity
Presentation time: April 22, 9 a.m.–noon PDT
Poster title: A cancer cell-intrinsic PAR1/MALT1/PD-L1 signaling pathway drives immune evasion in triple-negative breast cancer
Description: The study uncovers a signaling pathway that allows triple-negative breast cancer (TNBC) cells to evade attack by the immune system. The researchers characterized the signaling pathway and found a druggable target. These findings reveal a previously unrecognized mechanism of immune evasion and provide a framework for developing new therapeutic strategies for TNBC.
Presenter: Dong Hu, Ph.D., research scientist; Co-principal investigators: Linda McAllister, M.D. Ph.D., professor of pediatrics, Peter Lucas, M.D., Ph.D., professor of laboratory medicine and pathology

For more information, visit AACR.

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About Mayo Clinic
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.

About Mayo Clinic Comprehensive Cancer Center 
Designated as a comprehensive cancer center by the National Cancer Institute, Mayo Clinic Comprehensive Cancer Center is defining the cancer center of the future, focused on delivering the world's most exceptional patient-centered cancer care for everyone. At Mayo Clinic Comprehensive Cancer Center, a culture of innovation and collaboration is driving research breakthroughs in cancer detection, prevention and treatment to change lives.

Media contact:

• Julie Ferris-Tillman, Ph.D., Mayo Clinic Communications, newsbureau@mayo.edu

The post Mayo Clinic researchers present advances in immunotherapy, biomarkers and tumor biology at AACR 2026  appeared first on Mayo Clinic News Network.