Tumor mutation burden prediction model in Egyptian breast cancer patients based on next generation sequencing

Nassar, Auhood, Lymona, Ahmed M., Lotfy, Mai M., Youssef, Amira Salah El Din, Mohanad, Marwa, Manie, Tamer M., Youssef, Mina M.G. ORCID: https://orcid.org/0000-0002-6807-313X, Farahat, Iman G. and Zekri, Abdel Rahman N. (2021) Tumor mutation burden prediction model in Egyptian breast cancer patients based on next generation sequencing. Asian Pacific Journal of Cancer Prevention, 22 (7). pp. 2053-2059. ISSN 1513-7368

[thumbnail of Published_Version]
PDF (Published_Version) - Published Version
Available under License Creative Commons Attribution Non-commercial.

Download (822kB) | Preview


Objectives: This study aimed to identify the tumor mutation burden (TMB) value in Egyptian breast cancer (BC) patients. Moreover, to find the best TMB prediction model based on the expression of estrogen (ER), progesterone (PR), human epidermal growth factor receptor 2 (HER-2), and proliferation index Ki-67. Methods: The Ion AmpliSeq Comprehensive Cancer Panel was used to determine TMB value of 58 Egyptian BC tumor tissues. Different machine learning models were used to select the optimal classification model for prediction of TMB level according to patient’s receptor status. Results: The measured TMB value was between 0 and 8.12/Mb. Positive expression of ER and PR was significantly associated with TMB ≤ 1.25 [(OR =0.35, 95% CI: 0.04–2.98), (OR = 0.17, 95% CI= 0.02-0.44)] respectively. Ki-67 expression positive was significantly associated with TMB >1.25 than those who were Ki-67 expression negative (OR = 9.33, 95% CI= 2.07-42.18). However, no significant differences were observed between HER2 positive and HER2 negative groups. The optimized logistic regression model was TMB = −27.5 −1.82 ER – 0.73 PR + 0.826 HER2 + 2.08 Ki-67. Conclusion: Our findings revealed that TMB value can be predicted based on the expression level of ER, PR, HER-2, and Ki-67.

Item Type: Article
Uncontrolled Keywords: breast cancer,er,her-2,ki-67,pr,tumor mutation burden,epidemiology,oncology,public health, environmental and occupational health,cancer research,sdg 3 - good health and well-being ,/dk/atira/pure/subjectarea/asjc/2700/2713
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 14 Aug 2021 00:28
Last Modified: 29 Jun 2023 09:30
URI: https://ueaeprints.uea.ac.uk/id/eprint/81100
DOI: 10.31557/APJCP.2021.22.7.2053


Downloads per month over past year

Actions (login required)

View Item View Item