Literature DB >> 26049819

Imaging Genomics of Glioblastoma: Biology, Biomarkers, and Breakthroughs.

Safwan Moton1, Mohamed Elbanan, Pascal O Zinn, Rivka R Colen.   

Abstract

Glioblastoma is regarded as the most aggressive and most common primary malignant brain tumor in adults. Despite advancements in chemotherapy and radiotherapy, prognosis and overall survival of glioblastoma patients remain dismal. Recently, progresses in genetic profiling have increased our understanding of the underlying heterogenous molecular nature of this aggressive tumor. Several prognostic and predictive molecular biomarkers have been identified that have been linked to patient's survival and response to treatment, respectively. Imaging genomics represents a novel entity in clinical sciences that bidirectionally links imaging features with underlying molecular profile and thus can serve as a surrogate for noninvasive genomic correlation, prediction, and identification.

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Year:  2015        PMID: 26049819     DOI: 10.1097/RMR.0000000000000052

Source DB:  PubMed          Journal:  Top Magn Reson Imaging        ISSN: 0899-3459


  7 in total

1.  Integrative analysis of diffusion-weighted MRI and genomic data to inform treatment of glioblastoma.

Authors:  Guido H Jajamovich; Chandni R Valiathan; Razvan Cristescu; Sangeetha Somayajula
Journal:  J Neurooncol       Date:  2016-07-08       Impact factor: 4.130

2.  Radiogenomics correlation between MR imaging features and major genetic profiles in glioblastoma.

Authors:  Eun Kyoung Hong; Seung Hong Choi; Dong Jae Shin; Sang Won Jo; Roh-Eul Yoo; Koung Mi Kang; Tae Jin Yun; Ji-Hoon Kim; Chul-Ho Sohn; Sung-Hye Park; Jae-Kyung Won; Tae Min Kim; Chul-Kee Park; Il Han Kim; Soon Tae Lee
Journal:  Eur Radiol       Date:  2018-05-02       Impact factor: 5.315

Review 3.  Glioblastoma: Overview of Disease and Treatment.

Authors:  Mary Elizabeth Davis
Journal:  Clin J Oncol Nurs       Date:  2016-10-01       Impact factor: 1.027

4.  Thalamic Glioblastoma: Clinical Presentation, Management Strategies, and Outcomes.

Authors:  Yoshua Esquenazi; Nelson Moussazadeh; Thomas W Link; Koos E Hovinga; Anne S Reiner; Natalie M DiStefano; Cameron Brennan; Philip Gutin; Viviane Tabar
Journal:  Neurosurgery       Date:  2018-07-01       Impact factor: 4.654

5.  Machine-learning based classification of glioblastoma using delta-radiomic features derived from dynamic susceptibility contrast enhanced magnetic resonance images: Introduction.

Authors:  Jiwoong Jeong; Liya Wang; Bing Ji; Yang Lei; Arif Ali; Tian Liu; Walter J Curran; Hui Mao; Xiaofeng Yang
Journal:  Quant Imaging Med Surg       Date:  2019-07

Review 6.  Non-invasive tumor genotyping using radiogenomic biomarkers, a systematic review and oncology-wide pathway analysis.

Authors:  Robin W Jansen; Paul van Amstel; Roland M Martens; Irsan E Kooi; Pieter Wesseling; Adrianus J de Langen; Catharina W Menke-Van der Houven van Oordt; Bernard H E Jansen; Annette C Moll; Josephine C Dorsman; Jonas A Castelijns; Pim de Graaf; Marcus C de Jong
Journal:  Oncotarget       Date:  2018-04-13

7.  Comparative proteogenomic characterization of glioblastoma.

Authors:  Samia Asif; Rawish Fatima; Rebecca Krc; Joseph Bennett; Shahzad Raza
Journal:  CNS Oncol       Date:  2019-07-10
  7 in total

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