Researchers from City of Hope®, one of the largest and most advanced cancer research and treatment organizations in the United States with its National Medical Center ranked among the nation’s top ...

Minisymposia data will explore why cancers develop earlier, how tumors evade treatment and how AI is reshaping cancer research and immunotherapy.
SESSIONS: SY17, ADT06, 3993, 6745, 4037, 1298, LB238, LB389
LOS ANGELES: Researchers from City of Hope®, one of the largest and most advanced cancer research and treatment organizations in the United States with its National Medical Center ranked among the nation’s top cancer centers by U.S. News & World Report, will present new data at the AACR Annual Meeting 2026, sharing insights into cancer risk, treatment resistance and emerging therapeutic strategies across solid and blood cancers.
From April 17–22, expertise from City of Hope physicians and scientists will be spotlighted in 103 sessions, including in one major symposium, six minisymposia and three late-breaking poster abstracts.
As one of the world’s largest and most influential cancer research conferences, the annual meeting of the American Association for Cancer Research brings together scientists, clinicians and patient advocates from across the globe.
City of Hope investigators will highlight leading-edge expertise and research across the spectrum, including the following:
Together, the research underscores City of Hope’s efforts to translate leading‑edge science into more precise and effective approaches for patients who receive cancer care.
AI Reveals Microbiome Differences Linked to Early‑Onset Colorectal Cancer (3993)
City of Hope researchers will present new findings suggesting that among populations at increased risk, the gut microbiome differs between early‑ and late‑onset colorectal cancer. This line of investigation may explain why colorectal cancer has been rising in younger adults.
The study analyzed thousands of colorectal cancer tumor samples alongside microbiome data collected from patients with the disease. Researchers integrated these data with genomic profiles, clinical characteristics and social determinants of health, using AI tools to examine complex relationships across multiple data types.
The analysis showed that patients with early‑onset colorectal cancer had lower microbial diversity compared with those diagnosed later in life. Investigators also identified differences in microbial composition when stratifying patients by genetic ancestry, tumor mutation patterns, gene fusions, copy‑number alterations and social factors linked to health outcomes.
By applying AI‑guided integration, the researchers identified age‑specific microbial patterns that aligned with molecular and clinical features of disease - patterns that may have been difficult to detect using traditional analytic approaches alone. The findings highlighted the potential role of the gut microbiome in colorectal cancer development among younger patients.
“By bringing together microbiome data with genomic and clinical information, we were able to identify patterns that would have been difficult to detect using traditional approaches. This work demonstrates how AI can help us better understand complex factors that may contribute to earlier cancer development,” said Sophia Manjarrez, B.S., doctoral student at City of Hope’s Irell & Manella Graduate School of Biological Sciences, the study’s presenting author.
“This study reflects the growing importance of examining cancer through multiple lenses - biological, clinical and social - rather than in isolation. Understanding how these factors intersect may ultimately help inform more tailored approaches to cancer prevention, risk assessment and early detection,” said Enrique Velazquez‑Villarreal, M.D., Ph.D., study senior author and assistant professor in City of Hope’s Department of Integrative Translational Sciences.
New Molecular Pathway Identified in Colorectal Cancer Immune Resistance (6745)
City of Hope scientists will report the identification of a molecular pathway that helps explain why many colorectal cancers remain resistant to immunotherapy, particularly microsatellite-stable (MSS) tumors.
The researchers focused on the RNA-modifying enzyme NAT10 and its interaction with the oncogene MYC. They found that elevated NAT10 activity promoted immune evasion by enhancing autophagy-mediated loss of MHC class I molecules, which are essential for immune cells to recognize and target cancer.
High NAT10 expression was associated with immune-cold tumor environments with little to no immune cell activity and reduced predicted responses to immune checkpoint inhibitors. These effects were especially pronounced in MSS colorectal cancers, which account for the majority of cases and remain largely resistant to current immunotherapy approaches.
In preclinical models, disrupting the NAT10-MYC pathway restored immune signaling, increased immune cell infiltration and enhanced responses to immunotherapy, resulting in substantial tumor regression when combined with immune checkpoint blockade.
“These findings help explain why many colorectal tumors remain resistant to immunotherapy. By targeting this newly identified pathway, we may be able to improve immune recognition of tumors and expand the benefit of immunotherapy to more patients,” said Junyong Weng, Ph.D., the study’s presenting author and a City of Hope visiting scholar.
“Our findings identify a previously unrecognized MYC-NAT10-autophagy axis as a mechanism of immune evasion and immunotherapy resistance in colorectal cancer. MYC is a key driver of this disease but remains difficult to target therapeutically, while autophagy is essential for normal cell survival. Our study suggests that targeting tumor-specific NAT10 upregulation may offer a more selective strategy to suppress aberrant autophagy, prevent MHC-I loss and improve antitumor immune recognition,” said Ajay Goel, Ph.D., AGAF, senior author on the study and chair of City of Hope’s Department of Molecular Diagnostics and Experimental Therapeutics.
Targeting Cancer Metabolism Suppressed Acute Myeloid Leukemia in Preclinical Models (4037)
City of Hope researchers will present new data identifying a metabolic vulnerability in acute myeloid leukemia (AML), an aggressive blood cancer with limited treatment options and poor long‑term survival rates.
The study showed that leukemia cells depended on high levels of a protein called eIF4A1, which helped the cancer cells alter how they generate essential nutrients needed for survival. Blocking the protein eIF4A1 slowed the growth of leukemia cells, reduced their energy production and interfered with their ability to make new proteins.
Further analyses showed that eIF4A1 helped leukemia cells survive by supporting key enzymes involved in how the cells make and use nutrients. Disrupting this process weakened the cancer cells’ metabolism and slowed disease progression.
In several clinically relevant animal studies, blocking eIF4A1 reduced leukemia burden and helped models live longer. The effects were even stronger when the approach was combined with other drugs that target cancer cell metabolism, pointing to a potential new treatment strategy.
“We found that leukemia cells are heavily reliant on a specific protein to fuel their growth. By blocking eIF4A1, we were able to disrupt the cancer’s energy supply and slow the disease in preclinical studies, pointing to a promising new way to target AML,” said Xiaoxu Zhang, the study’s presenting author and a City of Hope visiting graduate researcher at Beckman Research Institute of City of Hope.
“This study shows the power of looking at cancer as an interconnected system, not just a single target. By combining molecular biology, metabolism and computational analysis, our team was able to uncover a hidden weakness in leukemia - an approach that reflects City of Hope’s leadership in systems‑level cancer research,” said Rui Su, Ph.D., senior author on the study and assistant professor at Beckman Research Institute of City of Hope.
AI Foundation Models Improved Prediction of Immune Targets for Cancer Therapy (1298)
Researchers will present a new AI approach designed to better predict how the immune system recognizes cancer cells - a key step in developing cancer vaccines and immune‑based therapies.
The approach used AI to better predict how immune cells recognize cancer cells by combining information about a protein’s shape with its genetic makeup, allowing the model to more accurately reflect how immune responses work.
Despite being trained on a relatively small dataset, the model achieved prediction accuracy comparable to leading tools currently used in the field. When combined with existing models, the approach further improved performance, highlighting the complementary value of structure‑ and sequence‑based methods.
The researchers say the AI model is especially useful in situations where data are scarce, such as rare patient immune types or newly identified cancer targets. The approach could help speed the development of personalized cancer vaccines and immune‑based treatments.
“One of the biggest challenges in immunotherapy is determining which peptides are actually presented by MHC molecules and can be recognized by T cells. By combining AlphaFold 3 structural predictions with a geometry-aware learning framework, our approach captures the physical interactions underlying peptide–MHC binding, allowing us to identify promising epitopes with higher accuracy even in low-data settings,” said Kamel Lahouel, Ph.D., assistant professor in TGen’s Early Detection and Prevention Division and the study’s presenting author.
“This work shows how combining biological insight obtained from sophisticated AI methods with experimental data can change how we approach immunotherapy and vaccine development. Rather than relying on massive experiments alone, which would take decades to perform and would never be complete, these new methods can provide meaningful predictions in a more efficient and scalable way,” said Cristian Tomasetti, Ph.D., senior author on the study, professor and director of City of Hope’s Center for Cancer Prevention, Early Detection and Monitoring, and professor in the Early Detection and Prevention Division at TGen.
Select Late-Breaking Poster Sessions from City of Hope:
Awards
About City of Hope
City of Hope's mission is to make hope a reality for all touched by cancer and diabetes. Founded in 1913, City of Hope has grown into one of the largest and most advanced cancer research and treatment organizations in the United States, and one of the leading research centers for diabetes and other life-threatening illnesses. City of Hope research has been the basis for numerous breakthrough cancer medicines, as well as human synthetic insulin and monoclonal antibodies. With an independent, National Cancer Institute-designated comprehensive cancer center that is ranked among the nation’s top cancer centers by U.S. News & World Report at its core, City of Hope’s uniquely integrated model spans cancer care, research and development, academics and training, and a broad philanthropy program that powers its work. City of Hope’s growing national system includes its Los Angeles campus, Orange County, California, campus, a network of clinical care locations across Southern California and cancer treatment centers and outpatient facilities in the Atlanta, Chicago and Phoenix areas. City of Hope’s affiliated group of organizations includes Translational Genomics Research Institute and AccessHopeTM. For more information about City of Hope, follow us on Facebook, X, YouTube, Instagram and LinkedIn.
Fonte: Business Wire
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