Related Experiment Video
Updated: May 25, 2026
A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions
Published on: April 18, 2025
Integrative survival-based molecular profiling of human pancreatic cancer
Timothy R Donahue1, Linh M Tran, Reginald Hill
1Department of Surgery, Division of General Surgery, David Geffen School of Medicine at University of California Los Angeles, Los Angeles, California, USA. tdonahue@mednet.ucla.edu
Purpose:
To carry out an integrative profile of human pancreatic ductal adenocarcinoma (PDAC) to identify prognosis-significant genes and their related pathways.
Experimental Design:
A concordant survival-based whole genome in silico array analysis of DNA copy number, and mRNA and miRNA expression in 25 early-stage PDAC was carried out. A novel composite score simultaneously integrated gene expression with regulatory mechanisms to identify the signature genes with the most levels of prognosis-significant evidence. The predominant signaling pathways were determined via a pathway-based approach. Independent patient cohorts (n = 148 and 42) were then used as in vitro validation of the array findings.
Results:
The composite score identified 171 genes in which expressions were able to define two prognosis subgroups (P = 3.8e-5). Eighty-eight percent (151 of 171) of the genes were regulated by prognosis-significant miRNAs. The phosphoinositide 3-kinase/AKT pathway and SRC signaling were densely populated by prognosis-significant genes and driven by genomic amplification of SRC and miRNA regulation of p85α and CBL. On tissue microarray validation (n = 148), p85α protein expression was associated with improved survival for all patients (P = 0.02), and activated P-SRC (Y418) was associated shorter survival for patients with low-grade histology tumors (P = 0.04). Interacting P-SRC and p85α revealed that they define two distinct PDAC patient subgroups (P = 0.0066). Furthering the importance of these pathways, CBL protein expression was associated with improved survival (P = 0.03) on a separate cohort (n = 42).
Conclusions:
These pathways and related genes may represent putative clinical biomarkers and possible targets of individualized therapy in the distinct patient subgroups they define.
