Prediction of Chemosensitivity in Multiple Primary Cancer Patients Using Machine Learning.

Journal: Anticancer research
Published Date: May 1, 2021

Abstract

BACKGROUND/AIM: Many cancer patients face multiple primary cancers. It is challenging to find an anticancer therapy that covers both cancer types in such patients. In personalized medicine, drug response is predicted using genomic information, which makes it possible to choose the most effective therapy for these cancer patients. The aim of this study was to identify chemosensitive gene sets and compare the predictive accuracy of response of cancer cell lines to drug treatment, based on both the genomic features of cell lines and cancer types.

Authors

  • Xianglan Zhang
    Department of Pathology, Yanbian University Medical College, Yanji, P.R. China.
  • M I Jang
    Department of Pathology, National Health Insurance Service Ilsan Hospital, Goyang, Republic of Korea.
  • Zhenlong Zheng
    Department of Dermatology, Yanbian University Hospital, Yanji, P.R. China.
  • Aihua Gao
    Department of Oncology, Yanbian University Hospital, Yanji, P.R. China.
  • Zhenhua Lin
    Department of Pathology and Cancer Research Center, Yanbian University Medical College, Yanji, P.R. China.
  • Ki-Yeol Kim
    BK21 PLUS Project, Department of Dental Education, Yonsei University College of Dentistry, Yonsei University, Seoul, Republic of Korea kky1004@yuhs.ac.

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