Program Director
Principal Investigator
Youping
Deng
Awardee Organization
University Of Hawaii At Manoa
United States
Fiscal Year
2022
Activity Code
R01
Early Stage Investigator Grants (ESI)
Not Applicable
Project End Date
NIH RePORTER
For more information, see NIH RePORTER Project 5R01CA230514-04
Circulating lipid and miRNA markers for early detection of breast cancer among women with abnormal mammograms
Breast cancer is the most common cancer among women in the world. When breast cancer is found in early stages, it can be effectively treated or even cured, but treating a patient in later stages is very difficult. Thus, early detection of breast cancer is critical. Mammography is the current gold standard for breast cancer screening; however, most women with abnormal mammograms are eventually found not to have breast cancer. Fewer than 5 per 1,000 women actually have the disease when they are screened. Therefore, most abnormal mammograms are false positives that require further investigations including expensive breast imaging and biopsies, which can cause psychological distress. According to the American Cancer Society (ACS), about 10% of women who have a mammogram will be called back for more tests, but only 8% to 10% of those women will need a biopsy and 80% of those biopsies turn out to be benign. Therefore, the vast majority of the women would have undergone unnecessary investigations. Our aim is to identify circulating lipid and miRNA signatures that can be used reliably as a companion diagnostic tool together with screening mammography to reduce the number of unnecessary follow-up investigations, especially invasive biopsy. In our preliminary studies, we have identified a panel of 15 plasma lipid species that were able to distinguish early stage of cancer from benign lesions with over 90% accuracy. Using a ratio based normalization method, we have also found 5 paired plasma miRNA ratios that differentiate breast cancer from benign samples with over 90% accuracy. In order to validate our existing markers and identify potential novel markers, as well as integrate lipid and miRNA markers to increase the accuracy for early detection of breast cancer, we propose the following aims: 1. Validate and test the predictive value of circulating lipid markers for early detection of breast cancer. 2. Establish circulating miRNA markers for early detection of breast cancer. 3. Integrate circulating lipid and miRNA markers for early detection of breast cancer.
Publications
- Zhang F, Wu X, Chen W, Deng Y. Editorial: Cancer Informatics Toward Precision Medicine. Frontiers in medicine. 2020 Nov 25;7:576611. doi: 10.3389/fmed.2020.576611. eCollection 2020. PMID: 33330533
- Rodriguez RM, Khadka VS, Menor M, Hernandez BY, Deng Y. Tissue-associated microbial detection in cancer using human sequencing data. BMC bioinformatics. 2020 Dec 3;21(Suppl 9):523. PMID: 33272199
- Rodriguez RM, Hernandez BY, Menor M, Deng Y, Khadka VS. The landscape of bacterial presence in tumor and adjacent normal tissue across 9 major cancer types using TCGA exome sequencing. Computational and structural biotechnology journal. 2020 Mar 13;18:631-641. doi: 10.1016/j.csbj.2020.03.003. eCollection 2020. PMID: 32257046
- Fu Y, Ling Z, Arabnia H, Deng Y. Current trend and development in bioinformatics research. BMC bioinformatics. 2020 Dec 3;21(Suppl 9):538. PMID: 33272214
- Kumar R, Deng Y, Fan JB, Wei L. Editorial: Early Detection and Diagnosis of Cancer. Frontiers in genetics. 2022 Mar 14;13:875421. doi: 10.3389/fgene.2022.875421. eCollection 2022. PMID: 35360854
- Gong T, Borgard H, Zhang Z, Chen S, Gao Z, Deng Y. Analysis and Performance Assessment of the Whole Genome Bisulfite Sequencing Data Workflow: Currently Available Tools and a Practical Guide to Advance DNA Methylation Studies. Small methods. 2022 Mar;6(3):e2101251. Epub 2022 Jan 22. PMID: 35064762
- Guo R, Chen Y, Borgard H, Jijiwa M, Nasu M, He M, Deng Y. The Function and Mechanism of Lipid Molecules and Their Roles in The Diagnosis and Prognosis of Breast Cancer. Molecules (Basel, Switzerland). 2020 Oct 21;25. (20). PMID: 33096860
- Foox J, Nordlund J, Lalancette C, Gong T, Lacey M, Lent S, Langhorst BW, Ponnaluri VKC, Williams L, Padmanabhan KR, Cavalcante R, Lundmark A, Butler D, Mozsary C, Gurvitch J, Greally JM, Suzuki M, Menor M, Nasu M, Alonso A, Sheridan C, Scherer A, Bruinsma S, Golda G, Muszynska A, Łabaj PP, Campbell MA, Wos F, Raine A, Liljedahl U, Axelsson T, Wang C, Chen Z, Yang Z, Li J, Yang X, Wang H, Melnick A, Guo S, Blume A, Franke V, Ibanez de Caceres I, Rodriguez-Antolin C, Rosas R, Davis JW, Ishii J, Megherbi DB, Xiao W, Liao W, Xu J, Hong H, Ning B, Tong W, Akalin A, Wang Y, Deng Y, Mason CE. The SEQC2 epigenomics quality control (EpiQC) study. Genome biology. 2021 Dec 6;22(1):332. PMID: 34872606