Unveiling the Biomarkers: Identifying Key Signatures for Cancer Hallmarks

Authors

DOI:

https://doi.org/10.4108/eetpht.10.5649

Keywords:

Biomarkers, Hallmark of Cancer, chemical biomarkers, protein biomarkers, karyotype biomarkers, Support Vector machine, Multilabel Classification, Biomedical features, MarkerDB dataset

Abstract

INTRODUCTION: Finding biomarkers that are closely associated with cancer-related traits is critical to the advancement of cancer research, especially when it comes to personalised treatment. The objective of this research is to explore multiple biomarker categories, including genetics, proteins, and chemicals, in order to better understand the complex terrain of cancer.

OBJECTIVES: Few of the objectives include examining a variety of biomarker types, such as chemical, protein, and genetic markers and determining which important biomarker signatures correspond to each cancer hallmark.

Also the study aims to perform a comparative analysis to show how the SVM model's features incorporating identified biomarkers improves classification performance.

METHODS: The study includes NLP and ML techniques for the identification and classification of biomarkers for the hallmark of cancer dataset.

RESULTS: The discovery of important biomarker signatures connected to every cancer hallmark is one of the study's primary findings. In addition, our new SVM-based classification model performed well in the multilabel text classification of PubMed abstracts, showing a significant improvement in performance when the biomarkers were used as features.

CONCLUSION: To sum up, this study makes a substantial contribution to the area of cancer research by identifying important biomarker signatures connected to many cancer hallmarks.

Downloads

Download data is not yet available.

References

M. R. M. Hussain et al., “BRAF gene: From human cancers to developmental syndromes,” Saudi J Biol Sci, vol. 22, no. 4, pp. 359–373, Jul. 2015, doi: 10.1016/j.sjbs.2014.10.002. DOI: https://doi.org/10.1016/j.sjbs.2014.10.002

D. Lai, S. Visser-Grieve, and X. Yang, “Tumour suppressor genes in chemotherapeutic drug response,” Biosci Rep, vol. 32, no. Pt 4, pp. 361–374, Aug. 2012, doi: 10.1042/BSR20110125. DOI: https://doi.org/10.1042/BSR20110125

“The role of BCL-2 family proteins in regulating apoptosis and cancer therapy - PMC.” Accessed: Aug. 06, 2023. [Online]. Available: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9597512/

C. D. Belair, T. R. Yeager, P. M. Lopez, and C. A. Reznikoff, “Telomerase activity: A biomarker of cell proliferation, not malignant transformation,” Proc Natl Acad Sci U S A, vol. 94, no. 25, pp. 13677–13682, Dec. 1997. DOI: https://doi.org/10.1073/pnas.94.25.13677

N. Nishida, H. Yano, T. Nishida, T. Kamura, and M. Kojiro, “Angiogenesis in Cancer,” Vasc Health Risk Manag, vol. 2, no. 3, pp. 213–219, Sep. 2006. DOI: https://doi.org/10.2147/vhrm.2006.2.3.213

T. A. Martin, L. Ye, A. J. Sanders, J. Lane, and W. G. Jiang, “Cancer Invasion and Metastasis: Molecular and Cellular Perspective,” in Madame Curie Bioscience Database [Internet], Landes Bioscience, 2013. Accessed: Aug. 06, 2023. [Online]. Available: https://www.ncbi.nlm.nih.gov/books/NBK164700/

“Lactate metabolism in human health and disease | Signal Transduction and Targeted Therapy.” Accessed: Aug. 06, 2023. [Online]. Available: https://www.nature.com/articles/s41392-022-01151-3

D. Hanahan and R. A. Weinberg, “The Hallmarks of Cancer,” Cell, vol. 100, no. 1, pp. 57–70, Jan. 2000, doi: 10.1016/S0092-8674(00)81683-9. DOI: https://doi.org/10.1016/S0092-8674(00)81683-9

“MarkerDB.” Accessed: Aug. 06, 2023. [Online]. Available: https://markerdb.ca/

“Genetic Marker,” Genome.gov. Accessed: Aug. 06, 2023. [Online]. Available: https://www.genome.gov/genetics-glossary/Genetic-Marker

N. Petrucelli, M. B. Daly, and T. Pal, “BRCA1- and BRCA2-Associated Hereditary Breast and Ovarian Cancer,” in GeneReviews® [Internet], University of Washington, Seattle, 2022. Accessed: Aug. 06, 2023. [Online]. Available: https://www.ncbi.nlm.nih.gov/books/NBK1247/

“Karyotype,” Genome.gov. Accessed: Aug. 06, 2023. [Online]. Available: https://www.genome.gov/genetics-glossary/Karyotype

A. R. Coelho et al., “Diabetes mellitus in HIV-infected patients: fasting glucose, A1c, or oral glucose tolerance test – which method to choose for the diagnosis?,” BMC Infect Dis, vol. 18, p. 309, Jul. 2018, doi: 10.1186/s12879-018-3221-7. DOI: https://doi.org/10.1186/s12879-018-3221-7

“Prostate-Specific Antigen - an overview | ScienceDirect Topics.” Accessed: Aug. 06, 2023. [Online]. Available: https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/prostate-specific-antigen

M. M. Sampaio et al., “Chronic myeloid leukemia-from the Philadelphia chromosome to specific target drugs: A literature review,” World J Clin Oncol, vol. 12, no. 2, pp. 69–94, Feb. 2021, doi: 10.5306/wjco.v12.i2.69. DOI: https://doi.org/10.5306/wjco.v12.i2.69

“Alzheimer’s: Is it in your genes? - Mayo Clinic.” Accessed: Aug. 06, 2023. [Online]. Available: https://www.mayoclinic.org/diseases-conditions/alzheimers-disease/in-depth/alzheimers-genes/art-20046552

“Environmental tobacco smoke exposure is associated with increased levels of metals in children’s saliva | Journal of Exposure Science & Environmental Epidemiology.” Accessed: Aug. 06, 2023. [Online]. Available: https://www.nature.com/articles/s41370-023-00554-w

[18] A. B. D′Avó Luís and M. K. Seo, “Has the development of cancer biomarkers to guide treatment improved health outcomes?,” Eur J Health Econ, vol. 22, no. 5, pp. 789–810, 2021, doi: 10.1007/s10198-021-01290-4. DOI: https://doi.org/10.1007/s10198-021-01290-4

V. K. Sarhadi and G. Armengol, “Molecular Biomarkers in Cancer,” Biomolecules, vol. 12, no. 8, p. 1021, Jul. 2022, doi: 10.3390/biom12081021. DOI: https://doi.org/10.3390/biom12081021

“Full Article.” Accessed: Aug. 06, 2023. [Online]. Available: http://2.mol.bio.msu.ru/biokhimiya/contents/v62/full/62111380.html

N. Murukesh, C. Dive, and G. C. Jayson, “Biomarkers of angiogenesis and their role in the development of VEGF inhibitors,” Br J Cancer, vol. 102, no. 1, pp. 8–18, Jan. 2010, doi: 10.1038/sj.bjc.6605483. DOI: https://doi.org/10.1038/sj.bjc.6605483

“scispaCy · spaCy Universe,” scispaCy. Accessed: Dec. 09, 2023. [Online]. Available: https://spacy.io/universe/project/scispacy

T. Gutschner and S. Diederichs, “The hallmarks of cancer: a long non-coding RNA point of view,” RNA Biol, vol. 9, no. 6, pp. 703–719, Jun. 2012, doi: 10.4161/rna.20481. DOI: https://doi.org/10.4161/rna.20481

S. Baker, A. Korhonen, and S. Pyysalo, “Cancer Hallmark Text Classification Using Convolutional Neural Networks,” p. 26.

S. Baker, A. Korhonen, and S. Pyysalo, “Cancer Hallmark Text Classification Using Convolutional Neural Networks,” p. 9.

Downloads

Published

05-04-2024

How to Cite

1.
Verma S, Sharan A. Unveiling the Biomarkers: Identifying Key Signatures for Cancer Hallmarks. EAI Endorsed Trans Perv Health Tech [Internet]. 2024 Apr. 5 [cited 2024 May 20];10. Available from: https://publications.eai.eu/index.php/phat/article/view/5649