\u201cEarly-onset colorectal cancer is a biologically and contextually distinct disease, and we need to approach it differently,\u201d Enrique Velazquez-Villarreal, MD, PhD, MPH, MS,<\/b> principal investigator and assistant professor in the department of integrative translational sciences at City of Hope, told Healio.<\/p>\n
\u201cFrom a clinical standpoint, this means moving toward more personalized strategies that integrate not only genomic data, but also microbiome profiles and patient-specific factors such as social determinants of health. These findings suggest that future screening, prevention and treatment approaches may need to be tailored based on age, ancestry and environmental context.\u201d<\/p>\n
\u2018Alarming\u2019 increase<\/h2>\n Overall colorectal cancer incidence in the U.S. declined 0.9% annually between 2013 and 2022, but it increased 3% per year among those aged 20 to 49 years, according to data from American Cancer Society\u2019s Colorectal Cancer Statistics 2026 report.<\/p>\n
\u201cEarly-onset colorectal cancer is increasing at an alarming rate worldwide, particularly among populations already at higher risk, including underserved and minority groups,\u201d Velazquez-Villarreal said. \u201cWhile we\u2019ve made significant progress in understanding the genetic drivers of colorectal cancer, we still don\u2019t fully understand why younger individuals are developing this disease more frequently.\u201d<\/p>\n
Prior studies have found the gut microbiome could have a \u201ccritical\u201d role in colorectal cancer development, Velazquez-Villarreal explained, noting the impact on immune response, inflammation and tumor biology.<\/p>\n
\u201cHowever, most studies have not integrated microbiome data with clinical, genomic and social determinants of health in a unified framework,\u201d he added. \u201cWe felt it was essential to take a more comprehensive, systems-level approach, leveraging artificial intelligence developed in my lab here at City of Hope \u2014 we call it AI-HOPE \u2014 to better understand how these factors interact, especially in early-onset disease.\u201d<\/p>\n
Researchers evaluated tumor samples from 2,715 patients with colorectal cancer from the NIH Cancer Moonshot COPECC PE-CGS Network as well as public data repositories.<\/p>\n
They also collected and analyzed stool samples from 23 patients from that cohort.<\/p>\n
Microbiome differences between early- and late-onset colorectal cancer served as the primary endpoint.<\/p>\n
\u2018Heterogenous microbial ecosystems\u2019<\/h2>\n Velazquez-Villarreal and colleagues observed early-onset samples had less microbial diversity than those of late-onset disease.<\/p>\n
\u201cThis suggests a less diverse gut ecosystem that may reflect or contribute to tumor-promoting conditions, such as immune dysregulation or metabolic imbalance,\u201d Velazquez-Villarreal said.<\/p>\n
They also found differences in specific microbial taxa.<\/p>\n
\u201cAcidaminococcaceae<\/i>, Veillonellaceae<\/i> and Lachnospiraceae<\/i> were among the most abundant taxa,\u201d Velazquez-Villarreal said. \u201cNotably, Prevotellaceae<\/i> abundance was increasing in early-onset colorectal cancer, indicating potential age-specific microbial enrichment patterns. These heterogeneous microbial ecosystems may reflect differences in host genetics, environmental exposures and life factors.\u201d<\/p>\n
Additionally, certain microbiome compositions had associations with tumor mutations, including APC<\/i>, TP53<\/i> and KRAS<\/i>, copy number variations and gene fusions.<\/p>\n
\u201cThese interactions extend further into the tumor microenvironment, where certain microbial patterns align with immune-related signatures and transcriptomic profiles derived from RNA sequencing, suggesting functional interplay between microbial communities and host gene expression,\u201d Velazquez-Villarreal said.<\/p>\n
Researchers found differences in microbiomes based on ancestry within Hispanic and Latino populations, as well as social determinants of health.<\/p>\n
\u201cFor example, higher vs. lower education levels correlated with shift in the relative abundance of key bacterial taxa,\u201d Velazquez-Villarreal said. \u201cWhen we stratified by BMI, this revealed distinct microbial abundance profiles between individuals with and without obesity, which indicated that metabolic status may modulate the tumor-associated microbiome.\u201d<\/p>\n
AI-HOPE identified connections between microbial taxa, genomic alternations, tumor stage and treatment type, as well.<\/p>\n
\u201cAI-guided case-control analyses further identified taxa such as Fusobacterium<\/i> and Parvimonas<\/i> as potential microbial biomarkers linked to disease characteristics,\u201d Velazquez-Villarreal said.<\/p>\n
Velazquez-Villarreal described the research as \u201can important first step,\u201d but noted several questions remained.<\/p>\n
\u201cFirst, we need larger, prospective studies to validate these findings and determine whether specific microbial signatures can serve as biomarkers for early detection or prognosis,\u201d he said. \u201cSecond, we want to better understand causality: Are these microbiome changes driving cancer development, or are they a consequence of tumor biology? Third, integrating longitudinal data will be critical to understand how the microbiome evolves over time and in response to treatment.<\/p>\n
\u201cFinally, one of our major goals is to develop AI-driven predictive models that can combine clinical, genomic, microbiome and social determinants of health data to identify individuals at highest risk and guide early intervention strategies.\u201d<\/p>\n
Velazquez-Villarreal and colleagues also are attempting to identify microbiome in different tissues, which could further enhance AI models and better predict disease development or recurrence.<\/p>\n
\u201cBy integrating microbiome science with highly autonomous artificial intelligence, developed from the ground up by our team of physician-scientists, genomic experts and computational specialists at the Velazquez-Villarreal Lab, and real-world patient data, we are beginning to uncover why colorectal cancer is rising in younger populations, while advancing our primary mission of developing early cancer detection tools to improve prevention and patient outcomes,\u201d Velazquez-Villarreal said.<\/p>\n
For more information:<\/h2>\n Enrique Velazquez-Villarreal, MD, PhD, MPH, MS,<\/b> can be reached at evelazquezvilla@coh.org.<\/p>\n\n
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Perspective<\/h2>\n Back to Top
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What I found most interesting was the use of the AI-HOPE platform to integrate microbiome data with multi-omics, clinical variables and social determinants of health.<\/default:p>This multidomain approach feels innovative, especially in high-risk populations. The alignment between age-specific microbial profiles and tumor molecular alterations adds biological plausibility, though I remain cautious because the stool sample size is still small.<\/default:p>Early-onset colorectal cancer shows a distinct gut microbiome signature characterized by reduced microbial richness and differences in composition that correlate with genetic ancestry, mutation patterns and social determinants of health.<\/default:p>This work also nicely demonstrates the value of AI-supported integrative analysis for uncovering patterns that might otherwise be missed. At the same time, the study is preliminary and clearly highlights the need for larger, well-powered studies to determine whether these microbial differences play a causal role in earlier disease onset.<\/default:p>The next steps should focus on expanding the stool microbiome cohort significantly to increase statistical power. Future research needs to validate these findings in independent cohorts, ideally incorporating longitudinal sampling.<\/default:p>Key questions that still need to be answered include: Are these microbial changes causative or simply a consequence of early tumorigenesis? Can specific microbial signatures serve as biomarkers for risk stratification or treatment response in early-onset colorectal cancer? And finally, whether microbiome modulation strategies could eventually improve outcomes in these patients.<\/default:p><\/p>\n
Disclosures: <\/strong> Biachi reports no relevant financial disclosures.
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Sources\/Disclosures<\/h3>\n Source: <\/h2>\n Manjarrez S, et al. Abstract 3993. Presented at: American Association for Cancer Research Annual Meeting; April 17-22, 2026; San Diego.<\/p>\n
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