Construction of a radiogenomic association map of pancreatic ductal adenocarcinoma

BMC Cancer

Research

Jayasuriya Senthilvelan¹  Neema Jamshidi²  David W. Dawson³  Timothy R. Donahue⁴  Michael D. Kuo⁵ 

[1] Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, 757 Westwood Ave, Suite 2125, 90095, Los Angeles, CA, USA;Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, 757 Westwood Ave, Suite 2125, 90095, Los Angeles, CA, USA;Jonsson Comprehensive Cancer Center, University of California, Los Angeles, CA, USA;Jonsson Comprehensive Cancer Center, University of California, Los Angeles, CA, USA;Department of Pathology, University of California, Los Angeles, CA, USA;Jonsson Comprehensive Cancer Center, University of California, Los Angeles, CA, USA;Department of Surgical Oncology, University of California, Los Angeles, CA, USA;Medical AI Laboratory Program, The University of Hong Kong, Hong Kong SAR, Hong Kong;

关键词: Pancreatic cancer;    Radiogenomics;    Network biology;    Tumor enhancement;    Non-invasive;    Glycerophospholipid metabolism;    Podosome assembly;    Mitophagy;    Infiltrative;    TGF-β;    Tumor-stroma interface;    Contrast-enhanced CT;    Transcriptome;   

DOI  :  10.1186/s12885-023-10658-z

 received in 2022-08-30, accepted in 2023-02-17,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundPancreatic adenocarcinoma (PDAC) persists as a malignancy with high morbidity and mortality that can benefit from new means to characterize and detect these tumors, such as radiogenomics. In order to address this gap in the literature, constructed a transcriptomic-CT radiogenomic (RG) map for PDAC.MethodsIn this Institutional Review Board approved study, a cohort of subjects (n = 50) with gene expression profile data paired with histopathologically confirmed resectable or borderline resectable PDAC were identified. Studies with pre-operative contrast–enhanced CT images were independently assessed for a set of 88 predefined imaging features. Microarray gene expression profiling was then carried out on the histopathologically confirmed pancreatic adenocarcinomas and gene networks were constructed using Weighted Gene Correlation Network Analysis (WCGNA) (n = 37). Data were analyzed with bioinformatics analyses, multivariate regression-based methods, and Kaplan-Meier survival analyses.ResultsSurvival analyses identified multiple features of interest that were significantly associated with overall survival, including Tumor Height (P = 0.014), Tumor Contour (P = 0.033), Tumor-stroma Interface (P = 0.014), and the Tumor Enhancement Ratio (P = 0.047). Gene networks for these imaging features were then constructed using WCGNA and further annotated according to the Gene Ontology (GO) annotation framework for a biologically coherent interpretation of the imaging trait-associated gene networks, ultimately resulting in a PDAC RG CT-transcriptome map composed of 3 stage-independent imaging traits enriched in metabolic processes, telomerase activity, and podosome assembly (P < 0.05).ConclusionsA CT-transcriptomic RG map for PDAC composed of semantic and quantitative traits with associated biology processes predictive of overall survival, was constructed, that serves as a reference for further mechanistic studies for non-invasive phenotyping of pancreatic tumors.

【 授权许可】

CC BY   
© The Author(s) 2023

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