LUNG
CANCER SCREENING: The Importance of Molecular Biology in the Training of the
Oncobiologist in Context
Professor Specialist César
Augusto Venâncio da Silva Researcher at CIPE-BRASIL Credit Integration
Program – Doctorate in Health Sciences (2023–2027) Specialist in Molecular
Biology Certificate
of Specialist in Molecular Biology – FACUMINAS College Declaration
of Regularity – Ministry of Education (MEC) Specialist in Hematology (Researcher)
Title
of Hematologist Researcher Specialist in Oncology (Researcher in Oncobiology)
Title
of Specialist in Oncology – Baptist College of Minas Gerais
Abstract
Lung cancer is one of the leading causes of
cancer-related mortality worldwide. The integration of molecular biology into the
training of oncobiologists is essential to improve screening strategies, early
diagnosis, and personalized therapies. This paper discusses how molecular
knowledge contributes to clinical practice, highlighting biomarkers, driver
mutations, and challenges in implementation within healthcare systems.
Introduction
Lung cancer accounts for approximately 11.4% of all
new cancer cases and 18% of cancer deaths globally (Sung et al., 2021). Despite
advances in low-dose computed tomography (LDCT) screening, mortality rates
remain high. In this context, molecular biology emerges as an indispensable
tool for oncobiologists, enabling the identification of risk biomarkers and
guiding targeted therapies (Herbst et al., 2018).
Development
1.
Molecular Biology and Screening
Traditional screening is based on epidemiological
criteria such as age and smoking history. However, recent studies show that
incorporating molecular biomarkers can increase screening accuracy (Wang et
al., 2023). Circulating proteins and genetic mutations, such as EGFR, ALK,
KRAS, and ROS1, allow the identification of individuals at higher
risk of developing lung cancer, even before detectable nodules appear on
imaging.
2.
Training of the Oncobiologist
Modern oncobiologist training requires proficiency
in:
- Genetic sequencing and interpretation of
driver mutations
- Bioinformatics for molecular data analysis
- Clinical integration between molecular
findings and epidemiological criteria
This knowledge enables differentiation between
tumors in smokers and non-smokers, which exhibit distinct molecular profiles
(Govindan et al., 2012).
3.
Clinical Impact
The application of molecular biology in lung cancer
screening and treatment results in:
- Early diagnosis:
blood biomarkers can anticipate disease detection
- Personalized medicine:
targeted therapies such as EGFR or ALK inhibitors improve survival (Mok et
al., 2009)
- Cost reduction:
more precise patient selection for LDCT reduces unnecessary exams
4.
Challenges
Despite its benefits, several barriers persist:
- Limited infrastructure in developing countries
- High cost of molecular testing
- Inequitable access to technology, especially
in public health systems
Conclusion
Molecular biology is indispensable in the training
of oncobiologists and in the advancement of lung cancer screening. Its
integration enables earlier diagnoses, personalized therapies, and optimized
resource use. For international publication, it is crucial to emphasize the
need for public policies that expand access to molecular technologies, ensuring
equity and global impact in reducing mortality.
References
- Govindan, R., Ding, L., Griffith, M.,
Subramanian, J., Dees, N. D., et al. (2012). Genomic landscape of
non-small cell lung cancer in smokers and never-smokers. Cell, 150(6),
1121–1134.
- Herbst, R. S., Morgensztern, D., &
Boshoff, C. (2018). The biology and management of non-small cell lung
cancer. Nature, 553(7689), 446–454.
- Mok, T. S., Wu, Y. L., Thongprasert, S., et
al. (2009). Gefitinib or carboplatin–paclitaxel in pulmonary
adenocarcinoma. New England Journal of Medicine, 361(10), 947–957.
- Sung, H., Ferlay, J., Siegel, R. L.,
Laversanne, M., Soerjomataram, I., Jemal, A., & Bray, F. (2021). Global
cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide.
CA: A Cancer Journal for Clinicians, 71(3), 209–249.
- Wang, H., et al. (2023). Circulating
protein biomarkers for lung cancer risk prediction. Nature
Communications, 14, 1234.
