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Professor Nancy Lan Guo delivered a lecture on Advancing AI in Precision Oncology

Foto da Professora Nancy Lan Guo durante sua apresentação.
Professor Nancy Lan Guo during the Seminar Advancing AI in Precision Oncology.

On Thursday, August 15, Professor Nancy Lan Guo delivered the seminar Advancing AI in Precision Oncology.

The presentation was part of the General Seminar Series of the Translational Oncology Center (CTO) at the Instituto do Câncer do Estado de São Paulo (ICESP), organized by the CTO Researchers. The Professor is currently in Brazil researching biomarkers at the CTO after receiving a Fulbright Distinguished Scholar grant.

In her presentation, Professor Guo discussed the impact that Artificial Intelligence (AI) software can have on Precision Oncology. According to her:

“With the use of AI, it is possible to better analyze data and make more accurate prognoses regarding the progression of cancer in patients.”

She detailed the research A Predictive 7-Gene Assay and Prognostic Protein Biomarkers for Non-small Cell Lung Cancer, which led to the creation of CATOS-LU, an AI software capable of predicting the likelihood of progression and metastasis in lung cancer, which is currently classified as a New Technology by the United States Food and Drug Administration (FDA).

CATOS-LU can accurately determine whether lung cancer patients are at high or low risk of progression or metastasis, depending on the expression combination of seven genes. With this information, it is possible to determine which lung cancer patients can be treated solely with surgeries, and which ones require additional treatments, such as chemotherapy (more aggressive) or immunotherapy (more expensive).

Professor Nancy Lan Guo’s research found that low-risk patients who underwent treatments such as chemotherapy had less successful outcomes compared to low-risk patients who only underwent surgeries. Guo’s group demonstrated that unnecessary chemotherapy treatment could lead to the selection of more migratory cells, inducing the appearance of metastases.

She also highlighted that non-cancerous tissues are sometimes mistaken for cancer, leading to unnecessary treatments that could be limited to surgery to remove these tissues. CATOS-LU can even identify which patients do not actually have cancer, thus avoiding inappropriate treatments.

CATOS-LU has already undergone clinical trials in the United States, but it is not yet available to patients.

Professor Guo also discussed the potential of Big Data, i.e., the analysis of large sets of complex data that, with the use of Artificial Intelligence, can be processed and analyzed to establish correlations and extract information that would not be easily grasped by humans.

This approach allows for the possibility of inputting large volumes of patient data and discovering which information is relevant for determining a patient’s prognosis or estimating the appropriateness and success of different treatments.

Thus, Big Data can be used to personalize cancer diagnosis, select the most appropriate treatments for patients, and contribute to the development of new drugs.

Professor Roger Chammas, Professor Maria Madalena Chimpolo, Professor Sergio Persival Baroncini Proença, Professor Nancy Lan Guo, Christiane Nagayassu, and Patrícia de Domenico Grijó.

 

In attendance were Professor Maria Madalena Chimpolo from Universidade Agostinho Neto in Angola, Professor Sergio Persival Baroncini Proença, President of the USP Agency for National and International Academic Cooperation (AUCANI) at USP, Christiane Nagayassu, and Patrícia de Domenico Grijó from the Fulbright Commission Brazil. Additionally, Professors from the Universidade de São Paulo (USP), Researchers from the CTO, as well as Master’s students, Doctoral students, and Undergraduate Research students from USP.

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