TY - GEN

T1 - Genes, Related to Trastuzumab and Lapatinib Resistance in Breast Cancer: Bioinformatic Analysis and Comprehensive Review

AU - Shifon, Sofia

AU - Evgenov, Ilya

AU - Karitskaya, Polina

AU - Chesnokova, Anna

AU - Karpets, Irina

AU - Tseilikman, David Mendl

N1 - © 2023 IEEE.

PY - 2023

Y1 - 2023

N2 - Trastuzumab and lapatinib are commonly used medicals for therapy of HER2-Enriched Breast Cancer. In this study, we discovered the genes, that make the clinical effort in the resistance to the therapy, with the usage of modern bioinformatic tools and meta-analysis of current tendencies in the clinic. We have searched for genes, which expression levels can predict the response to trastuzumab and lapatinib, found the differences between sensitive and resistant groups. Final gene signatures were chosen from the pool of differentially expressed genes. We have merged the results with the data from open sources and made a gene network. Finally, we have found genes which expression is reliably connected with the sensitivity or resistance to the therapy and discovered previously not well-known most likely potentially significant genes. Our research will be modified and refined. The results will be of interest both to the scientific community in terms of a more detailed description of the signatures we have identified, and useful in the clinic to provide a more targeted approach in the treatment of breast cancer.

AB - Trastuzumab and lapatinib are commonly used medicals for therapy of HER2-Enriched Breast Cancer. In this study, we discovered the genes, that make the clinical effort in the resistance to the therapy, with the usage of modern bioinformatic tools and meta-analysis of current tendencies in the clinic. We have searched for genes, which expression levels can predict the response to trastuzumab and lapatinib, found the differences between sensitive and resistant groups. Final gene signatures were chosen from the pool of differentially expressed genes. We have merged the results with the data from open sources and made a gene network. Finally, we have found genes which expression is reliably connected with the sensitivity or resistance to the therapy and discovered previously not well-known most likely potentially significant genes. Our research will be modified and refined. The results will be of interest both to the scientific community in terms of a more detailed description of the signatures we have identified, and useful in the clinic to provide a more targeted approach in the treatment of breast cancer.

KW - HER2

KW - bioinformatics

KW - breast cancer

KW - lapatinib

KW - trastuzumab

UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85180361243&origin=inward&txGid=35dfe19ec6f0c73abfcc6e2dcc317da7

UR - https://www.mendeley.com/catalogue/89a1d479-b009-3461-b0b6-3266f13f4768/

U2 - 10.1109/CSGB60362.2023.10329855

DO - 10.1109/CSGB60362.2023.10329855

M3 - Conference contribution

SN - 9798350307979

T3 - 2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2023 - Proceedings

SP - 248

EP - 254

BT - 2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2023 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine

Y2 - 28 September 2023 through 29 September 2023

ER -