Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Integrated clustering analysis of UPCI 08-144 correlative studies

Hou, Surui (2018) Integrated clustering analysis of UPCI 08-144 correlative studies. Master's Thesis, University of Pittsburgh. (Unpublished)

Submitted Version

Download (6MB) | Preview


Melanoma, which is developed from uncontrolled growth of melanocytes, is one of the most dangerous form of skin cancer and causes thousands of deaths every year. Cure rate for early stage melanoma is fairly high (99% 5-year survival rate), while prognosis of locally and distant metastatic melanoma is very poor. Immunotherapy has shown promising efficacy in late-stage tumors. However, only a portion of the patients respond to the treatment and some experience severe immune-related side effects. Identifying patient subgroups that response differently is of great interest.
UPCI 08-144 is a single arm neoadjuvant ipilimumab clinical trial for patients with American Joint Committee on Cancer (AJCC) stage IIIB-C melanoma. Different types of biomarker data (cytokine data, flow cytometry data, mRNA data and microRNA) were obtained. We applied traditional single level analysis as well as integrative clustering analysis to identify subgroups with distinct genetic character. Although we did not identify subgroups that are significantly associated with either the prognosis or the occurrence of adverse events in patients treated with ipilimumab, partially due to small sample size, we gained valuable experiences in the application of integrated clustering analysis which will guide future study design and practice.
Public health significance: Heterogeneous response to cancer treatment has been a main obstacle in treating cancer patients. Identification of patient subgroups with regard to treatment efficacy and toxicity using various biological data has been a challenging task. Integrative clustering analysis could prove to be a promising tool in solving this piece of puzzle, which could provide a valuable tool in personalized cancer treatment, which will significantly improve the survival of cancer patients.


Social Networking:
Share |


Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Hou, Suruisuh27@pitt.edusuh27
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Thesis AdvisorLin, Yanyal14@pitt.eduyal14
Committee MemberRen, Dianxudir8@pitt.edudir8
Committee MemberWang, Honghow8@pitt.eduhow8
Committee MemberTarhini,
Date: 17 September 2018
Date Type: Publication
Defense Date: 14 June 2018
Approval Date: 17 September 2018
Submission Date: 3 June 2018
Access Restriction: 5 year -- Restrict access to University of Pittsburgh for a period of 5 years.
Number of Pages: 64
Institution: University of Pittsburgh
Schools and Programs: School of Public Health > Biostatistics
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: Integrated clustering analysis, clinical data, melanoma
Date Deposited: 17 Sep 2018 20:14
Last Modified: 01 Jul 2023 05:15


Monthly Views for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item