What is the clinical evidence from this study?

Study design: Other. Population: Cancer research education. Intervention: STEMM education programs integrating multi-omics and AI.

What question did this study set out to answer?

The aim is to prepare future scientists for cancer complexity by integrating advanced analytical techniques in education.

April 5, 2026

Abstract 7667: Integrating multi-omics and AI-driven approaches into STEMM education to advance cancer research training.

Key Result

Scalable STEMM education programs integrating multi-omics and AI-driven approaches were developed across multiple learner levels to strengthen participation in cancer research.

Key Points

The aim is to prepare future scientists for cancer complexity by integrating advanced analytical techniques in education.
Developed educational programs incorporating multi-omics and AI methods.
Implemented training for teachers and students at various educational levels.
Engaged secondary teachers in hands-on multi-omics training through BRITE.
Involved undergraduate and graduate trainees in multi-omics workflows and cancer methodologies.
Created high-school programs culminating in a student research symposium.
BRITE program equips teachers with the tools to translate cancer research into classroom practices.
C-REP engages students in advanced cancer research methodologies and analytics.
IMPACT Medical Scholar Program introduces medical students to cancer research techniques.
High-school programs foster early interest in cancer research and analytics.

Structured PICO

Population

Secondary-school teachers, undergraduate/graduate/PharmD trainees, medical students, and high-school students

Intervention

Scalable STEMM education programs integrating multi-omics and artificial intelligence (including BRITE, C-REP, and IMPACT Medical Scholar Program)

Integrating multi-omics and AI into STEMM education across multiple learner levels provides a scalable model to strengthen the pipeline for cancer research training.

Abstract

Abstract Preparing future scientists to address the complexity of cancer requires early exposure to advanced analytical methods and transdisciplinary thinking. We developed scalable STEMM education programs that integrate multi-omics and artificial intelligence into cancer research training across multiple learner levels. Central to this effort is the Biotechnology Research Incubator for Teachers (BRITE), an NIH R25 Science Education Partnership Award program providing secondary-school teachers with hands-on multi-omics training rooted in cancer biology. By incorporating genomics, proteomics, and data-driven interpretation, BRITE equips teachers to translate authentic cancer research practices into classroom learning. Building on this foundation, the NCI-funded P20 Cancer Research Education Program (C-REP) engages undergraduate and graduate/PharmD trainees in multi-omics workflows, tumor signaling pathways, and computational analyses. We also established the IMPACT Medical Scholar Program, which introduces medical students to cancer research methodologies, advanced analytics, and patient-centered communication. To broaden the early pipeline, we created high-school programs that use AI-assisted adapted primary literature and culminate in a student research symposium. Collectively, these programs provide a scalable model for integrating advanced technologies into STEMM education to strengthen participation in cancer research. Citation Format: Shixia Huang, . Integrating multi-omics and AI-driven approaches into STEMM education to advance cancer research training abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 7667.

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