You are here

Article Text

Article menu
Download PDFPDF
Clinical Gastroenterology
IDDF2024-ABS-0336 Identification of plasma protein biomarkers for colorectal cancer diagnosis and prognosis
  1. Dong Hang1,
  2. Xinyi Liu1,
  3. Chengqu Fu1,
  4. Le Wang2,
  5. Junyan Miao1,
  6. Jiacong Li1,
  7. Hongxia Ma1,
  8. Guangfu Jin1,
  9. Ni Li3,
  10. Zhibin Hu1,
  11. Xiaosheng He4,
  12. Lingbin Du2,
  13. Hongbing Shen1
  1. 1Department of Epidemiology, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China
  2. 2Zhejiang Provincial Office for Cancer Prevention and Control, Zhejiang Cancer Hospital, Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China
  3. 3Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
  4. 4Department of Colorectal Surgery, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, the Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China

Abstract

Background The incidence and mortality of colorectal cancer (CRC) have been steadily rising in many countries. There is an urgent need to identify convenient, reliable biomarkers for CRC early diagnosis and precise prognostic prediction.

Methods Untargeted plasma proteomics profiling by liquid chromatography coupled to tandem mass spectrometry was performed among a cohort of 321 participants as a discovery set (i.e., 107 CRC cases, 107 advanced adenomas (AA) cases, and 107 healthy controls (HC)), as well as a cohort of 353 participants as a validation set (i.e., 136 CRC, 81 AA, and 136 HC) (IDDF2024-ABS-0336 Figure 1). Random forest algorithm and the least absolute shrinkage and selection operator regression were adopted for the selection of protein biomarkers and the construction of diagnostic and prognostic models.

Results We identified 133 significantly altered proteins in CRC vs. HC, 15 in AA vs. HC, and 32 in CRC vs. AA. A model of 8 plasma proteins (COMP, C1QTNF3, H4C1, LRG1, PGM1, PKP1, PTPRJ, and TEK) showed great performance in discriminating CRC from HC, with an AUC of 0.932 (95% confidence interval [CI]: 0.857-0.989) in the validation set. A model of 6 proteins (CNTN4, COMP, IGFBP5, LDHA, PGAM1, and SPP1) showed the optimal ability to discriminate AA from HC, with an AUC of 0.816 (95% CI: 0.689-0.932) (IDDF2024-ABS-0336 Figure 2). Moreover, we established a prognostic model of 8 proteins (ANKRD26, APOA4, C9, FCGRT, LGALS1, PDGFRB, PGD, and PON1), showing an AUC of 0.705 for 3-year and 0.690 for 5-year disease-free survival in the validation set of CRC patients (IDDF2024-ABS-0336 Figure 3).

Abstract IDDF2024-ABS-0336 Figure 1
Abstract IDDF2024-ABS-0336 Figure 1

Study flowchart.

Abstract IDDF2024-ABS-0336 Figure 2
Abstract IDDF2024-ABS-0336 Figure 2

Receiver operator characteristic analysis of protein biomarkers for colorectal cancer (CRC) vs. healthy controls (HC) (A), advanced adenomas (AA) vs. HC (B), and CRC vs. AA (C).

Abstract IDDF2024-ABS-0336 Figure 3
Abstract IDDF2024-ABS-0336 Figure 3

Evaluate the prognostic model in the discovery and validation datasets. (A) Kaplan-Meier curves of disease-free survival (DFS) for colorectal cancer patients in the low-risk group (blue line) or high-risk group (red line). (B) The predictive efficiency of the DFS-Score was assessed by the time-dependent receiver operator characteristic analysis.

Conclusions The identified profile of protein biomarkers may contribute to the development of powerful blood-based tests for CRC early detection and prognostic monitoring, ultimately enabling precision interventions and improved patient outcomes.

https://doi.org/10.1136/gutjnl-2024-IDDF.306

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.