| Title: | Pre-diagnostic plasma proteomics profile for hepatocellular carcinoma |
| Journal: | Journal of the National Cancer Institute |
| Published: | 1 May 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38688524/ |
| DOI: | https://doi.org/10.1093/jnci/djae079 |
Publication 9781
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
OBJECTIVE: Proteomics may discover pathophysiological changes related to hepatocellular carcinoma (HCC), an aggressive and lethal type of cancer with low sensitivity for early-stage diagnosis.</p>
DESIGN: We measured 1,305 pre-diagnostic (median 12.7 years) SOMAscan proteins from 54 pairs of healthy individuals who subsequently developed HCC and matched non-HCC controls from the Nurses' Health Study (NHS) and the Health Professionals Follow-up Study (HPFS). Candidate proteins were validated in the independent, prospective UK Biobank Pharma Proteomics Project (UKB-PPP).</p>
RESULTS: In NHS/HPFS, we identified 56 elevated proteins in HCC with absolute fold-change >1.2 and Wald test P < .05 in conditional logistic regression analysis. Ingenuity Pathway Analysis identified enrichment of pathways associated with cell viability, adhesion, proteolysis, apoptosis, and inflammatory response. Four proteins, chitinase-3-like protein 1, growth/differentiation factor 15, interleukin-1 receptor antagonist protein, and E-selectin, showed strong positive associations with HCC and were thus validated by ELISA (odds ratio ranged 2.48-14.7, all P < .05) in the NHS/HPFS and by Olink platform (hazard ratio ranged 1.90-3.93, all P < .05) in the UKB-PPP. Adding these four proteins to a logistic regression model of traditional HCC risk factors increased the area under the curve (AUC) from 0.67 to 0.87 in the NHS/HPFS. Consistently, model AUC was 0.88 for HCC risk prediction in the UKB-PPP.</p>
CONCLUSION: However, the limited number of HCC cases in the cohorts necessitates caution in interpreting our findings, emphasizing the need for further validation in high-risk populations.</p>
11 Authors
- Xinyuan Zhang
- Longgang Zhao
- Long H Ngo
- Simon T Dillon
- Xuesong Gu
- Michelle Lai
- Tracey G Simon
- Andrew T Chan
- Edward L Giovannucci
- Towia A Libermann
- Xuehong Zhang
1 Application
| Application ID | Title |
|---|---|
| 87303 | Improving liver health in humans: Elucidating the role of genetics, biomarkers, and environment in liver biology, etiology, progression, and prognosis |
Enabling scientific discoveries that improve human health