SMART PLATFORM FOR BIOMARKER-FREE PRECISION ONCOLOGY WITHOUT THE USE OF BIOMARKERS

Authors

DOI:

https://doi.org/10.61229/mpj.v2i1.33

Keywords:

Breast Cancer, Spectroscopy, Artificial intelligence, Surgical Margins, Machine Learning

Abstract

Introduction: Breast cancer is considered the most common neoplasm among women, with approximately 74,000 cases estimated in Brazil for the year 2023(1,5). Given the complexity of this neoplasm, the therapeutic approach depends on the stage of the disease and the specific type of tumor identified(2). Complete surgical resection with clear margins of the tumor is crucial for a better prognosis for the patient(3-4). Careful evaluation of the margins during surgery is essential for successful treatment and to prevent cancer recurrence. Therefore, there is a need to improve strategies that contribute to the removal of tumors with cancer-free margins.

Objective: This project aims to clinically validate the tumor classification model called “Process for Classifying Cells by Lineage and Use,” which utilizes spectroscopic measurements obtained from the interaction of radiation with biological cell samples. These measurements will be processed by an artificial intelligence model to differentiate cell lineages and detect various cancerous lineages.

Materials and Methods: Tumor tissue will be fixed in buffered formalin and subsequently embedded in paraffin to form blocks. Then, six sections of 3 to 4 micrometers in thickness will be made and placed on slides, with one stained with Hematoxylin and Eosin and the others analyzed by spectroscopy(6). Patient data will be collected via electronic medical records and correlated with the obtained analyses. Finally, the data will be analyzed using artificial intelligence and machine learning to generate an intelligent predictive system(7). This study was approved by the institutional ethics committee CAAE: 70737223.0.0000.5121.

Preliminary Results: To date, a biorepository of 22 patients, representative of normal and paired tumor tissue, has been obtained, totaling 132 slides.

Conclusion: Spectroscopy analysis may contribute to optimizing the characterization of surgical margins for breast cancer patients, improving prognosis, and reducing the process costs and time required for diagnosis.

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Author Biographies

Ana Beatriz Ramos Do Nascimento, Federal University of Minas Gerais, Department of Physics; Teaching, Research, and Innovation Center of the Mário Penna Institute

Second degree completed at Colégio Nossa Senhora do Amparo in Barra Mansa RJ, with graduation in progress at Universidade FUMEC and Scientific Initiation at Instituto Mario Penna in Belo Horizonte MG

Paulo Guilherme de Oliveira Salles, Teaching, Research, and Innovation Center of the Mário Penna Institute.

Graduated in Medicine from the Faculty of Medicine of the Federal University of Minas Gerais (FM-UFMG, 1995). Residency in Clinical Medicine at Hospital Municipal Odilon Behrens (1996) and in Pathology at Hospital das Clínicas da FM-UFMG (1999). Master in Medical Pathology from FM-UFMG (2001). Research Fellow (Urological Pathology) at Emory University (Atlanta, Georgia, USA - 2002). MBA in Health Systems Management from IBMEC-MG (2007). PhD in Medicine from FM-UFMG (2010). Member of the Magazine's editorial board: Mário Penna Journal (2022). Senior pathologist in laboratories in Belo Horizonte (MG) and São Paulo (SP). Scientific Director of the Education and Research Institute (IEPI) of the Mário Penna Institute (Belo Horizonte - MG).

Paulo Henrique Ribeiro Amaral, : Federal University of Minas Gerais, Department of Physics;

He has a degree in Physics from the Federal University of Minas Gerais (2013), a master's degree in Physics from the Federal University of Minas Gerais (2014) and a PhD in Physics from the Federal University of Minas Gerais (2019). He has experience in the area of ​​Physics, with an emphasis on Atomic and Molecular Physics, working mainly on the following topics: positron, non-adiabatic corrections, high-resolution spectroscopy of light molecules, materials physics, artificial intelligence and data science.

Letícia da Conceição Braga, Startup OncoTag; Teaching, Research, and Innovation Center of the Mário Penna Institute.

Biologist, Master in Genetics from the Federal University of Minas Gerais, PhD in Health Sciences from the Faculty of Medicine of Botucatu/UNESP and Post-Doctorate in Drug Discovery in Oncology. MBA in Business Management from USP-ESALQ. Co-founder of the startup OncoTag. With his experience, he has fought for the development of scientific entrepreneurship and innovation in Brazil. She is currently coordinator of the Basic and Translational Research Laboratory at the Mário Penna Institute, working in the lines of research in Precision Oncology and Translational Medicine, with an emphasis on the following topics: tumor genomics and transcriptomics, bioinformatic analyzes of DNA and RNA sequences and analysis of differential gene expression and signaling related to prognostic and predictive factors of radiochemotherapy treatment. Professor accredited as a voluntary collaborator of the Postgraduate Course in Morphofunctional Sciences at UFSJ and Genetics at UFMG. She received several awards and honorable mentions as a scientist and entrepreneur, among which the following stand out: II Fleury Innovation Award, Highlight at Demoday InovAtiva Brasil, Carlos Ribeiro Diniz Award (Funed), UNA Teaching Merit and Francisco Mauro Salsano Award - Human Genetics. Allied Doctoral Scientist member of the American Society of Oncology (ASCO) and member of the EVA Brazilian Gynecological Tumor Group.

Juan Carlos Gonzáles Pérez , Federal University of Minas Gerais, Department of Physics;

He has a degree in Physics - Universidad de La Havana (1994), a master's degree in Physics - Universidad de La Havana (1996) and a PhD in Physics from the Federal University of Minas Gerais (2000). He is currently an adjunct professor at the Federal University of Minas Gerais. He has experience in the area of ​​Physics, with an emphasis on Structural Characterization and Semiconductor Optics, working mainly on the following topics: semiconductors, semiconductor devices, MBE, TEM, SEM and AFM.

References

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Vicini FA, Kestin L, Huang R, Martinez A. Does local recurrence affect the rate of distant metastases and survival in patients with early-stage breast carcinoma treated with breast-conserving therapy? Cancer. 2003 Feb 3;97(4):910–9. DOI: https://doi.org/10.1002/cncr.11143

Jobsen JJ, van, Ong F, Meerwaldt JH. Differences in outcome for positive margins in a large cohort of breast cancer patients treated with breast-conserving therapy. Acta Oncologica. 2007 Jan 1;46(2):172–80. DOI: https://doi.org/10.1080/02841860600891325

Wöckel A, Albert US, Janni W, Scharl A, Kreienberg R, Stüber T. Clinical practice guideline: The screening, diagnosis, treatment, and follow-up of breast cancer. Deutsches Aerzteblatt Online. 2018 May 4. DOI: https://doi.org/10.3238/arztebl.2018.0316

Outubro Rosa 2023 [Internet]. Instituto Nacional de Câncer - INCA. [cited 2024 Jan 12]. Available from: https://www.gov.br/inca/pt-br/assuntos/campanhas/2023/outubro-rosa#:~:text=O%20C%C3%A2ncer%20de%20ma

Espectroscopia [Internet]. astro.if.ufrgs.br. [cited 2024 Jan 12]. Available from: http://astro.if.ufrgs.br/telesc/espectroscopia.html#:~:text=Em%20uma%20imagem%20%C3%B3ptica%2C%20em

Amaral PHR, González Pérez JC, de Andrade LM. Processo para classificação de células quanto à linhagem celular e uso. Departamento de Física da UFMG; BR 10 2021 025248 0 A2.

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Published

2024-08-16

How to Cite

Villar, P., Ramos Do Nascimento, A. B., de Oliveira Salles, P. G., Ribeiro Amaral, P. H., da Conceição Braga, L., & Gonzáles Pérez , J. C. (2024). SMART PLATFORM FOR BIOMARKER-FREE PRECISION ONCOLOGY WITHOUT THE USE OF BIOMARKERS . Mário Penna Journal, 2(1), 121–123. https://doi.org/10.61229/mpj.v2i1.33

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Vol. 2 No. 1 (2024): Mário Penna Journal

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