Literature DB >> 24516257

Multifunctional imaging signature for V-KI-RAS2 Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations in colorectal cancer.

Kenneth A Miles1, Balaji Ganeshan, Manuel Rodriguez-Justo, Vicky J Goh, Zia Ziauddin, Alec Engledow, Marie Meagher, Raymondo Endozo, Stuart A Taylor, Stephen Halligan, Peter J Ell, Ashley M Groves.   

Abstract

UNLABELLED: This study explores the potential for multifunctional imaging to provide a signature for V-KI-RAS2 Kirsten rat sarcoma viral oncogene homolog (KRAS) gene mutations in colorectal cancer.
METHODS: This prospective study approved by the institutional review board comprised 33 patients undergoing PET/CT before surgery for proven primary colorectal cancer. Tumor tissue was examined histologically for presence of the KRAS mutations and for expression of hypoxia-inducible factor-1 (HIF-1) and minichromosome maintenance protein 2 (mcm2). The following imaging parameters were derived for each tumor: (18)F-FDG uptake ((18)F-FDG maximum standardized uptake value [SUVmax]), CT texture (expressed as mean of positive pixels [MPP]), and blood flow measured by dynamic contrast-enhanced CT. A recursive decision tree was developed in which the imaging investigations were applied sequentially to identify tumors with KRAS mutations. Monte Carlo analysis provided mean values and 95% confidence intervals for sensitivity, specificity, and accuracy.
RESULTS: The final decision tree comprised 4 decision nodes and 5 terminal nodes, 2 of which identified KRAS mutants. The true-positive rate, false-positive rate, and accuracy (95% confidence intervals) of the decision tree were 82.4% (63.9%-93.9%), 0% (0%-10.4%), and 90.1% (79.2%-96.0%), respectively. KRAS mutants with high (18)F-FDG SUVmax and low MPP showed greater frequency of HIF-1 expression (P = 0.032). KRAS mutants with low (18)F-FDG SUV(max), high MPP, and high blood flow expressed mcm2 (P = 0.036).
CONCLUSION: Multifunctional imaging with PET/CT and recursive decision-tree analysis to combine measurements of tumor (18)F-FDG uptake, CT texture, and perfusion has the potential to identify imaging signatures for colorectal cancers with KRAS mutations exhibiting hypoxic or proliferative phenotypes.

Entities:  

Keywords:  KRAS protein; colonic neoplasms; comparative study; diagnostic imaging; human

Mesh:

Substances:

Year:  2014        PMID: 24516257     DOI: 10.2967/jnumed.113.120485

Source DB:  PubMed          Journal:  J Nucl Med        ISSN: 0161-5505            Impact factor:   10.057


  32 in total

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Review 2.  Radiogenomics Based on PET Imaging.

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3.  Comparison of Contrast-Enhanced CT and [18F]FDG PET/CT Analysis Using Kurtosis and Skewness in Patients with Primary Colorectal Cancer.

Authors:  Franca Wagner; Yahya Ali Hakami; Geoffrey Warnock; Gabriel Fischer; Martin W Huellner; Patrick Veit-Haibach
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Review 4.  Targeting metabolic reprogramming in KRAS-driven cancers.

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Review 5.  Novel imaging techniques of rectal cancer: what do radiomics and radiogenomics have to offer? A literature review.

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6.  Somatic Mutations Drive Distinct Imaging Phenotypes in Lung Cancer.

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Journal:  Cancer Res       Date:  2017-05-31       Impact factor: 12.701

7.  Can CT-based radiomics signature predict KRAS/NRAS/BRAF mutations in colorectal cancer?

Authors:  Lei Yang; Di Dong; Mengjie Fang; Yongbei Zhu; Yali Zang; Zhenyu Liu; Hongmei Zhang; Jianming Ying; Xinming Zhao; Jie Tian
Journal:  Eur Radiol       Date:  2018-01-15       Impact factor: 5.315

8.  Development and validation of a MRI-based radiomics signature for prediction of KRAS mutation in rectal cancer.

Authors:  Yanfen Cui; Huanhuan Liu; Jialiang Ren; Xiaosong Du; Lei Xin; Dandan Li; Xiaotang Yang; Dengbin Wang
Journal:  Eur Radiol       Date:  2020-01-15       Impact factor: 5.315

9.  A computed tomography (CT)-derived radiomics approach for predicting primary co-mutations involving TP53 and epidermal growth factor receptor (EGFR) in patients with advanced lung adenocarcinomas (LUAD).

Authors:  Ying Zhu; Yu-Biao Guo; Di Xu; Jing Zhang; Zhen-Guo Liu; Xi Wu; Xiao-Yu Yang; Dan-Dan Chang; Min Xu; Jing Yan; Zun-Fu Ke; Shi-Ting Feng; Yang-Li Liu
Journal:  Ann Transl Med       Date:  2021-04

Review 10.  The use of molecular imaging combined with genomic techniques to understand the heterogeneity in cancer metastasis.

Authors:  R Chowdhury; B Ganeshan; S Irshad; K Lawler; M Eisenblätter; H Milewicz; M Rodriguez-Justo; K Miles; P Ellis; A Groves; S Punwani; T Ng
Journal:  Br J Radiol       Date:  2014-03-06       Impact factor: 3.039

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