Development and validation of a cancer stem cell-related signature for prognostic prediction in pancreatic ductal adenocarcinoma

Abstract

Background Cancer stem cells (CSCs) are crucial to malignant behavior and poor prognosis of pancreatic ductal adenocarcinoma (PDAC). In recent years, CSC biology has been widely studied, but practical prognostic signatures based on CSC-related genes have not been established and reported in PDAC. Methods This signature was developed and validated in seven independent PDAC datasets. MTAB-6134 cohort was used as training set, while one Chinese local cohort and five other public cohorts were used for external validation. CSC-related genes with credible prognostic roles were selected to form the signature, and its predictive performance was evaluated by Kaplan-Meier survival, receiver operating characteristic (ROC), and calibration curves. Correlation analysis was employed to clarify the potential biological characteristics. Results A robust signature comprising DCBLD2, GSDMD, PMAIP1, and PLOD2 was developed. It could classify patients into high-risk and low-risk groups, and high risk patients had significantly shorter overall survival (OS) and disease-free survival (DFS) compared with low risk patients. Calibration curves and Cox regression analysis demonstrated the powerful predictive performance. ROC curves showed an improved survival prediction provided by this model. Functional analysis revealed positive association between risk score and CSC marker. These results had cross-dataset compatibility. Conclusions We established a novel four-gene signature based on CSC-related genes which could serve as a powerful prognostic tool in PDAC. Impact This signature can offer potential help for further improving current TNM staging system, and providing data for the development of novel personalized therapeutic strategies in the future.

A Novel DNA Replication-Related Signature Predicting Recurrence After R0 Resection of Pancreatic Ductal Adenocarcinoma: Prognostic Value and Clinical Implications

“…Advancements in gene expression profiles derived from various high throughput technologies have improved our understanding of genetic and molecular alternations in PDAC. In recent years, many prognostic gene signatures have been developed by assessing crucial biological processes in PDAC progression, including autophagy ( Yue et al, 2020 ), cell stemness ( Feng et al, 2020 ) and immunological pathways ( Wu et al, 2020 ). These models provided information for predicting OS.…”

Transcriptomic Profiling Identifies DCBLD2 as a Diagnostic and Prognostic Biomarker in Pancreatic Ductal Adenocarcinoma

“…In gastric cancer, DCBLD2 is downregulated by epigenetic modi cation, and it exhibits suppressive role in cancer cell proliferation and invasion [8]. In the context of PDAC, the elevated expression of DCBLD2 is correlated with poor clinical outcome, indicating DCBLD2 may serve as an appealing biomarker for PDAC diagnosis and prognosis [9,10]. However, these PDAC studies fail to evaluate the diagnostic and prognostic potential of DCBLD2 from a holistic and multidimensional perspective.…”

Identifying tumor cells at the single cell level

“…Automatic characterization of tumor cells can be used for automation of neoantigen prediction [20,21]. It would enable automatic characterization of tumor cell states, such as tumor stem cells [22]. Computational delineation of cancer cells would greatly expedite biomarker discovery, and the development of companion diagnostic tools for measuring drug efficacy, during preclinical and clinical drug development.…”