Identifying prognostic subgroups of luminal-A breast cancer using denoising autoencoders = 디노이징 오토인코더를 이용한 luminal-A 아형 유방암의 예후적 하위 그룹 식별

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Luminal-A breast cancer is a subtype with the largest number of patients, about 40% of all breast cancer patients. The biggest characteristic of luminal-A breast cancer patients is a wide range of variation in prognosis for endocrine therapy. Therefore, this research divides the luminal-A breast cancer patients into the two distinct prognostic subgroups. The latent features generated through denoising autoencoders that extract and compress gene expression patterns of luminal-A breast cancer patients identify the two prognostic subgroups. The significance difference in overall survival between two subgroups are shown via log-rank test that is a hypothesis test to compare the survival distributions of two samples. In addition, through biological pathway analysis, it is found that the autophagy-lysosome pathways are more activated in the better prognostic subgroups. It is expected that this research can be used for personalized breast cancer treatment.
Advisors
Lee, Doheonresearcher이도헌researcher
Description
한국과학기술원 :바이오및뇌공학과,
Publisher
한국과학기술원
Issue Date
2020
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 바이오및뇌공학과, 2020.2,[v, 50 p. :]

Keywords

breast cancer▼aautoencoders▼aprognosis▼asubgroups▼aautophagy; 유방암▼a오토인코더▼a예후▼a하위그룹▼a자가포식

URI
http://hdl.handle.net/10203/283840
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=909921&flag=dissertation
Appears in Collection
BiS-Theses_Master(석사논문)
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