C2PO Interviews

C2PO interviews Professor Nancy Lan Guo

Between July and August 2024, C2PO welcomes Nancy Lan Guo, a Chinese-American Professor and Researcher.

Nancy completed her undergraduate studies in Biochemistry and Molecular Biology at Peking University in Beijing, China, where she was born. She then moved to the United States, where she earned her Master’s and Ph.D. in Computer Science, both from West Virginia University.

After nineteen years as a Professor at West Virginia University, Nancy recently started as a SUNY Empire Innovation Professor of Artificial Intelligence and Machine Learning at Binghamton University, part of the State University of New York System (SUNY).

In addition, in 2020, she founded Sostos Inc., a technology and health analysis services company for precision medicine.

She came to Brazil after receiving a Fulbright Scholarship to discover biomarkers and is developing this research at the Translational Oncology Center (CTO) at the Cancer Institute of São Paulo State (ICESP).

Nancy granted an interview to C2PO.

 

C2PO: You started your studies in China and later moved to the US. Now you are researching in Brazil. Does this multicultural experience influence your work?

Professor Nancy Lan Guo: Changing countries was a significant experience because it required me to adapt to a new culture and a new language at a very young age. I was already curious and eager to learn, but this made me more adaptable and more willing and open to experiment with new ideas. 

This is something I can utilize in my research, as I feel confident stepping out of my comfort zone and exploring new paths. Additionally, this experience has helped me understand the importance of having diverse perspectives and the value of multidisciplinary approaches in advancing research.

 

C2PO: Have you always been interested in research? What was your path to researching cancer through a computational perspective?

Professor Nancy Lan Guo: Yes, I already had an interest in research. I did my undergraduate studies in Biochemistry and Molecular Biology. In college, I participated in a national laboratory plant genetics project, which involved isolating plant genes to help crops better withstand drought. This experience made me realize my interest in genome studies, and it also made me want to study the human genome for its potential to contribute to medical advances.

When I finished my undergraduate degree, I moved to the United States to pursue a PhD in Biochemistry. But I realized it wasn’t exactly what I wanted to do. So I decided to leave the Biochemistry program and start a new Master’s in Computer Science, focusing on using ECG (Electrocardiogram) signals to predict the onset of adverse heart events, which was already an application of computing to healthcare. I had to start computer science classes from scratch because this subject was not part of my undergraduate studies. I studied hard to become an excellent student. And a professor told me that, in addition to mastering the technical part, I also had a good intuition for computational algorithms, which gave me more confidence to pursue this path.

Right after my Master’s, I started my Ph.D. in Computer and Information Science, working on a project for NASA developing algorithms that could predict which components of equipment were most likely to fail on missions. At the same time, I also had another experience at a private company where I dealt with patient data.

These experiences gave me the tools for what I started doing later, the application of computing, now termed ‘artificial intelligence (AI)’, to cancer research.

 

C2PO: Can you tell us more about your current cancer research?

Professor Nancy Lan Guo: I work on identifying biomarkers.

Currently, I am working on developing AI software that can scan large genomic datasets and predict the best approach for cancer screening, diagnosis, prognosis, and treatment, allowing for a customized approach for an individual’s cancer.

With our AI technology, we can discover biomarkers to tailor treatment plans for each patient. For instance, using these biomarkers, we can identify which patients will benefit from a particular therapy and predict their response to available drugs, so they do not waste time and money and suffer from side effects of the drugs that they will not respond to.  We are also able to identify potential new drugs and new indications of existing drugs efficiently with a much reduced cost and an  increased chance of success in clinical trials. This is done by using AI to analyze patient comprehensive genome data, i.e., multi-omics, and interpret the important molecular pathways and networks in a cancer type.

 

C2PO: How is it possible to create algorithms (of a mathematical nature) to predict the progression or metastasis of cancer (of a biological nature)?

Professor Nancy Lan Guo: There is a very complex intersection between mathematics and biology in that case.

Through research, it is possible to identify genes that, in interaction, are responsible for progression and metastasis in cancer. It is crucial to understand that not all of a person’s genes are important for determining the chance of progression or metastasis, so it is necessary to identify which specific genes, in interaction, play an important role in this outcome.

During a research focused in lung cancer, it was possible to reduce the number of genes of interest to about 200 genes, and then to identify the 7 determinant genes to assess whether a patient might have progression and metastasis.

From analyzing the interactions between these 7 genes, it is possible to reach a very conclusive answer about the chances of metastasis in a patient with lung cancer. This means that patients with less severe cases, which can be resolved with surgery alone, do not need to undergo more aggressive treatments like chemotherapy. 

This research became the Cancer Treatment Optimization Solutions (CATOS), currently evaluated as a “Novel Technology” by the Food and Drug Administration (FDA). CATOS-LU, focused on lung cancer, was successfully tested on 1,641 patients, including a randomized phase III clinical trial.

 

C2PO: You are also the founder and CEO of a company, Sostos Inc. Can you talk about this other role?

Professor Nancy Lan Guo: The founding of Sostos is directly linked to CATOS: CATOS-LU, focused on lung cancer, is the first product of Sostos.

A major difficulty in research is overcoming the barrier between the research lab and clinical application, that is, turning successful research into a product that can benefit patients, and doing it with safety.

To make CATOS a reality and ensure it reaches patients, I had to make a decision: hand over control of the research to an established company, or start my own company and maintain control over the research. I was hesitant to start the company because I didn’t see myself as an entrepreneur. But I was encouraged by fellow researchers who had done the same, received support from the National Science Foundation (NSF), and also obtained financial support from the National Institutes of Health (NIH), a U.S. government agency. Once again, curiosity and a willingness to learn were crucial for this to happen.

 

C2PO: How do you evaluate the impacts of technologies such as Artificial Intelligence and Big Data in advancing cancer diagnosis and treatment?

Professor Nancy Lan Guo: To give an idea, the Human Genome Project, conducted in the 1990s and completed in the early 2000s, required $3 billion for genetic sequencing. Today, a health plan can cover the costs of sequencing a cancer patient’s genome. The use of AI brings the possibility of analyzing a patient’s genome and defining the best treatment strategies considering that person’s unique characteristics. It can be used to define the best treatment at the best time, with safety.

The application of Big Data in oncology also has a significant impact. With the ability to collect and analyze enormous volumes of data, it is possible to identify patterns and correlations that were previously invisible, and make predictions to prevent tumor progression.

Furthermore, AI can be used to assist doctors in remote locations that lack well-developed infrastructure.

 

C2PO: Besides AI and Big Data, is there any other technology you are paying attention to?

Professor Nancy Lan Guo: I am very interested in material science, notably nanotechnology. Nanotechnology has incredible potential for use in precision oncology treatments.

 

C2PO: Do you believe we will be able to cure the diverse forms of cancer?

Professor Nancy Lan Guo: Yes, I do believe we will be able to do so. I think the greatest example is childhood leukemia, which is now a highly curable disease with a complete remission rate of 90%. That was only possible thanks to researchers discovering that arsenic trioxide (ATO) could treat patients. It will take time and research, but I’m optimistic about cures for other types of cancer.

 

C2PO: Lastly, what advice would you give to students pursuing a career in research?

Professor Nancy Lan Guo: Always remain curious and eager to learn. Don’t be afraid to try new things or to cross current barriers. Eventually, all your experiences will pay off. These include all your successes and temporary setbacks.

 

C2PO: Thank you for the interview! Is there anything else you would like to add?

Professor Nancy Lan Guo: It is my honor and privilege to become a Fulbright US Scholar for Brazil. I appreciate the hospitality of the Universidade de Sao Paulo as the host institute, and I also want to thank Professor Roger Chammas for the kind reception at his lab.

I hope to further develop our collaborative project here, benefiting local and global cancer patient populations. I look forward to interacting with the students and faculty in my future education and research efforts.

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