Oops, you're using an old version of your browser so some of the features on this page may not be displaying properly.

MINIMAL Requirements: Google Chrome 24+Mozilla Firefox 20+Internet Explorer 11Opera 15–18Apple Safari 7SeaMonkey 2.15-2.23

Poster session 10

909P - A multi-cancer early detection model based on liquid biopsy of multi-omics biomarkers: A proof of concept study (PROMISE study)

Date

10 Sep 2022

Session

Poster session 10

Topics

Secondary Prevention/Screening

Tumour Site

Presenters

Qiang Gao

Citation

Annals of Oncology (2022) 33 (suppl_7): S417-S426. 10.1016/annonc/annonc1061

Authors

Q. Gao1, C. wang2, X. Yang3, S. Fang3, Y. Zhang3, G. Wang3, F. Liu3, X. wen3, J. zhao3, G. Zhou3, B. li3, S. cai3, Z. Zhang3, J. Fan4

Author affiliations

  • 1 Department Of Liver Surgery And Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, 200032 - Shanghai/CN
  • 2 /, Burning Rock Biotech, 100068 - Guangzhou/CN
  • 3 /, Burning Rock Biotech, 510300 - Guangzhou/CN
  • 4 Department Of Liver Surgery And Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai/CN

Resources

Login to get immediate access to this content.

If you do not have an ESMO account, please create one for free.

Abstract 909P

Background

Liquid biopsy is promising for cancer early detection to reduce mortality, particularly for those cancers without effective screening paradigms. The Pan-canceR early detectiOn by Multi-omIcS biomarkErs study (PROMISE, NCT04972201) is a prospective multicenter case-control study to assess the performance of the multi-cancer detection blood test (MCDBT) in the early detection of nine cancers in the lung, colorectum, liver, esophagus, pancreas, head and neck, ovary, and biliary tract.

Methods

Blood samples were prospectively collected from cancer patients and non-cancer individuals. A targeted cell-free DNA (cfDNA) methylation panel of ∼490,000 CpG sites, a 168-gene mutation panel, and a 16-protein assay were applied. Participants stratified by age and clinical status were split into training (n = 981) and test sets (n = 492). The MCDBT models were developed on the training set and then validated on the test set.

Results

In the test set, specificities of the methylation, mutation, and protein based MCDBT models were 99.2% (95% CI: 97.0‒99.9%), 99.1% (96.8‒99.9%), and 99.6% (97.7‒100.0%), respectively (Table). The sensitivities for the three MCDBT models were 72.4% (66.5‒77.8%), 51.7% (44.1‒59.2%) and 47.8% (40.8‒54.9%), respectively. The multi-omics MCDBT model combining the methylation, mutation, and protein markers yielded a higher sensitivity of 79.0% (73.5‒83.8%) at a specificity of 97.9% (95.1‒99.3%). The accuracies of the top-one and top-two predicted origins were 75.3% (68.4‒81.3%) and 90.9% (85.8‒94.6%), respectively. Table: 909P

Performance of the MCDBT models

Performance MCDBT models
Multi-omics Methylation Mutation Protein
Specificity (95% CI) 97.9% (95.1‒99.3%) 99.2% (97.0‒99.9%) 99.1% (96.8‒99.9%) 99.6% (97.7‒100%)
Sensitivity (95% CI)
Total 79.0% (73.5‒83.8%) 72.4% (66.5‒77.8%) 51.7% (44.1‒59.2%) 47.8% (40.8‒54.9%)
Stage I 61.9% (48.8‒73.9%) 50.8% (37.9‒63.6%) 33.3% (19.6‒49.5%) 32.1% (19.9‒46.3%)
Stage II 70.2% (56.6‒81.6%) 63.2% (49.3‒75.6%) 38.9% (23.1‒56.5%) 38.6% (24.4‒54.5%)
Stage III 86.7% (76.8‒93.4%) 80.0% (69.2‒88.4%) 53.7% (39.6‒67.4%) 50.8% (38.1‒63.4%)
Stage IV 95.2% (86.5‒99.0%) 93.5% (84.3‒98.2%) 75.0% (60.4‒86.4%) 72.1% (56.3‒84.7%)

Conclusions

The methylation-based MCDBT model exhibited a superior sensitivity at a high specificity in the early detection of nine cancers. The multi-omics model improved sensitivity with a minimal impact on specificity. A further expanded study (NCT04817306) is currently recruiting.

Clinical trial identification

NCT04972201.

Editorial acknowledgement

Legal entity responsible for the study

Qiang Gao.

Funding

Guangzhou Burning Rock Dx Co., Ltd.

Disclosure

C. Wang, X. Yang, S. Fang, Y. Zhang, G. Wang, F. Liu, X. Wen, J. Zhao, G. Zhou, B. Li, S. Cai, Z. Zhang: Financial Interests, Institutional, Full or part-time Employment: Burning Rock Biotech. All other authors have declared no conflicts of interest.

This site uses cookies. Some of these cookies are essential, while others help us improve your experience by providing insights into how the site is being used.

For more detailed information on the cookies we use, please check our Privacy Policy.

Customise settings
  • Necessary cookies enable core functionality. The website cannot function properly without these cookies, and you can only disable them by changing your browser preferences.