Abstract 2529
Background
Compared with quantification of messenger RNA, a protein level quantification allows for more relevant clinical outcome predictions and the identification of potential therapeutic targets. The aim of this study was to identify a novel protein level signature that was associated with overall survival in patients with resected pancreatic ductal adenocarcinoma (PDAC).
Methods
Data of 105 patients with resected PDAC were retrieved from TRGAted. Reverse-phase protein array (RPPA) quantification data of 218 proteins were collected. By using the LASSO regression model, a protein-level-based classifier was built. Time-dependent receiver operating characteristic (ROC) analysis was used to assess the prognostic accuracy of the classifier. Survival curves were compared by using the Kaplan-Meier analysis.
Results
Using the LASSO model, we built a classifier based on four proteins: BAK, IGFBP2, PDL1, and BRAF-pS445. Survival analysis revealed IGFBP2 and BRAF-pS445 were two favourable prognostic markers, and BAK and PDL1 were unfavourable prognostic markers. Using the classifier, we were able to classify patients between those at high risk of disease progression (high-risk group) and those at low risk of disease progression (low-risk group). Progression-free survival was significantly different between these two groups (11.7 vs 19.9 months for high-risk and low-risk groups, respectively; P < 0.0001). The median overall survival was 13.1 and 36.7 months for the high-risk and low-risk groups, respectively (hazard ratio [HR]: 4.09; 95% CI: 2.39 - 6.98; P < 0.0001). Five-year survival rate was 0% for the high-risk group, and 46% for the low-risk group. The prognostic accuracy (area under the ROC curve) of the classifier were 0.75, 0.77, and 0.81 at 1, 3, and 5 years, respectively. Multivariate Cox regression analysis showed that the classifier was an independent prognostic factor (P < 0.0001).
Conclusions
This protein-level classifier is a novel prognostic tool in patients with resected PDAC. It may facilitate individualized management of patients with this disease.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Jie Hua.
Funding
The National Science Fund for Distinguished Young Scholars of China (grant number 81625016).
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
3392 - Post-hoc analysis of the nintedanib exposure-response relationships in the CHIVA trial in advanced ovarian cancer: (a GINECO study)
Presenter: Skerdi HAVIARI
Session: Poster Display session 2
Resources:
Abstract
714 - The feasibility and efficacy of gonadotropin-releasing hormone agonists for prevention of chemotherapy-induced ovarian insufficiency in patient with malignant ovarian germ cell tumors
Presenter: Min Kyu Kim
Session: Poster Display session 2
Resources:
Abstract
1753 - Ex vivo cytotoxicity and in vivo antitumor activity of a novel highly selective STAT3 inhibitor YHO-1701 for ovarian and endometrial cancer
Presenter: Kosei Hasegawa
Session: Poster Display session 2
Resources:
Abstract
3739 - Mutational landscapes and tumor mutational burden expression in endometrial cancer
Presenter: Yingli Zhang
Session: Poster Display session 2
Resources:
Abstract
2109 - Clinical features and frequency of mismatch repair protein deficiency in ovarian clear cell and endometrioid carcinoma patients.
Presenter: Kazuhiro Takehara
Session: Poster Display session 2
Resources:
Abstract
4554 - Prospective study evaluating white adipose tissue inflammation and clinicopathologic features in endometrial cancer
Presenter: Lea Moukarzel
Session: Poster Display session 2
Resources:
Abstract
3645 - Cancer-specific survival with or without adjuvant chemotherapy in high-risk stage I endometrial cancer
Presenter: Jenny Ko
Session: Poster Display session 2
Resources:
Abstract
3394 - Pembrolizumab in Patients with MSI-H Advanced Endometrial Cancer from the KEYNOTE-158 Study
Presenter: David Omalley
Session: Poster Display session 2
Resources:
Abstract
3388 - Who drops out of cervical cancer screening? Results from the EDIFICE 6 survey
Presenter: Thibault de La Motte Rouge
Session: Poster Display session 2
Resources:
Abstract
2485 - Identification of a RNA-Seq Based Signature to Improve Prognostic for Uterine Sarcoma
Presenter: Jian-Guo Zhou
Session: Poster Display session 2
Resources:
Abstract