A team of researchers at New Mexico State University has been making strides to provide more clues about underlying factors during cancer progression through an ongoing partnership with the Fred Hutchinson Cancer Center in Seattle, Washington. This collaboration will focus on a critical aspect of cancer biology: the metabolic adaptation of cancer cells.
Soyoung Jeon, associate professor of applied statistics in the NMSU College of Business, said the collaboration was possible through the Partnership for the Advancement of Cancer Research, a long-standing collaboration between NMSU and the Fred Hutchinson Cancer Research Center.
"We developed a cancer research grant proposal titled 'Systemic Understanding of Cellular Mechanisms of Metabolic Adaptations in Cancer' based on our shared research goal of elucidating these metabolic adaptation mechanisms," Jeon said. "This project, sponsored by the National Cancer Institute, aims to investigate the metabolic variables governing the initiation of adaptation and to identify the cellular processes that drive these adaptive changes."
Jeon explained the project aims to use polyomic profiling – multiple layers of omics data such as RNA-seq, DNA methylation, and protein levels aggregated in the cancer database – and patient metadata, combined with bioinformatic analyses and machine learning approaches.
"This is to understand the biological mechanisms used by cancer cells to enact adaptive metabolic reprogramming," she said. "The project also aims to identify determinants in health disparities associated with metabolic alterations in cancer using patient cancer datasets."
The NMSU research team consists of three graduate students with diverse backgrounds in statistics and bioinformatics: Agnes Duah and Farzaneh Karimi, master's students in the applied statistics program in the College of Business; and Stephanie Reinert, a recent master's graduate in bioinformatics from the College of Arts and Sciences.
Each student contributes to the team's ability to analyze and interpret metabolic expression data with their statistical background.
"Stephanie worked with me to analyze cancer data using Python algorithms. Agnes and Farzaneh work on this project as research assistants and analyze diverse types of patient cancer datasets to identify signatures of metabolic adaptations in cancer cells," Jeon said.
The three-year research project began in September 2023. During the second year, Jeon said the integration of diverse types of polyomic patient datasets will begin in order to conduct statistical analysis and uncover patterns of metabolic adaptations during cancer progression.
"In the final year, we aim to achieve the goals of the partnership of contributing to the local communities by disseminating our research findings and experiences to the Fred Hutch and NMSU communities, scientific societies, and underrepresented populations," Jeon said.
One of the other top goals for the team is to provide educational opportunities such as short courses or data analysis workshops across NMSU to increase underrepresented students engaged in areas of cancer research.
"Through diverse interactions with multiple organizations and underserved communities, the research team will actively disseminate our findings and cancer research education, leading to greater participation of underrepresented scientists in cancer research," Jeon explained.
Jeon added that this multidisciplinary project combines expertise in state-of-the-art laboratory techniques and statistical applications across two institutions by incorporating students and trainees from different backgrounds and experiences.
"The NMSU and Fred Hutch teams meet monthly for joint group meetings to update on current progress, exchange ideas, receive feedback, and address experimental or analytical bottlenecks," Jeon said. "A particularly rewarding aspect of this research is seeing how the process of transferring knowledge of cancer metabolism and statistics between research teams strengthens the capabilities of both researchers and students."
Now in its second year, the NMSU research team has identified genes with significant differences in protein abundance between tumor and normal samples and have been exploring several biological pathways involved in tumor-upregulated genes. The team will continue to work on analyzing omics data to find significant factors driving metabolic expression changes in various types of cancer data using machine learning approaches.
"For example, racial and ethnic differences will be analyzed for specific cancer types-clear cell renal cell carcinoma, breast cancer, colon cancer, and glioblastoma," Jeon explained. "We expect to elucidate whether genetic factors by race or ethnicity and clinical features associated with metabolic adaptations in cancer cell progression."
As for future student involvement in this collaborative project, Jeon said that anyone from current undergraduate to graduate students who want to learn more about omics data analysis and biostatistics can join this cancer research opportunity.
"You will learn how to access different types of cancer data and understand multiple omics data structures," Jeon said. "You will also be exposed to various statistical methods for omics data analysis."
For more information about this project or to get involved, contact Jeon at
The full article can be seen at https://newsroom.nmsu.edu/news/nmsu-research-team-focuses-on-cancer-biology-through-partnership--increase-underrepresented-student-/s/06c38794-27e0-4892-b59b-e8b26e534113
