Literature DB >> 33001791

Decoding Genes: Current Update on Radiogenomics of Select Abdominal Malignancies.

Venkata S Katabathina1, Haneen Marji1, Lokesh Khanna1, Nisha Ramani1, Sireesha Yedururi1, Anil Dasyam1, Christine O Menias1, Srinivasa R Prasad1.   

Abstract

Technologic advances in chromosomal analysis and DNA sequencing have enabled genome-wide analysis of cancer cells, yielding considerable data on the genetic basis of malignancies. Evolving knowledge of tumor genetics and oncologic pathways has led to a better understanding of histopathologic features, tumor classification, tumor biologic characteristics, and imaging findings and discovery of targeted therapeutic agents. Radiogenomics is a rapidly evolving field of imaging research aimed at correlating imaging features with gene mutations and gene expression patterns, and it may provide surrogate imaging biomarkers that may supplant genetic tests and be used to predict treatment response and prognosis and guide personalized treatment options. Multidetector CT, multiparametric MRI, and PET with use of multiple radiotracers are some of the imaging techniques commonly used to assess radiogenomic associations. Select abdominal malignancies demonstrate characteristic imaging features that correspond to gene mutations. Recent advances have enabled us to understand the genetics of steatotic and nonsteatotic hepatocellular adenomas, a plethora of morphologic-molecular subtypes of hepatic malignancies, a variety of clear cell and non-clear cell renal cell carcinomas, a myriad of hereditary and sporadic exocrine and neuroendocrine tumors of the pancreas, and the development of targeted therapeutic agents for gastrointestinal stromal tumors based on characteristic KIT gene mutations. Mutations associated with aggressive phenotypes of these malignancies can sometimes be predicted on the basis of their imaging characteristics. Radiologists should be familiar with the genetics and pathogenesis of common cancers that have associated imaging biomarkers, which can help them be integral members of the cancer management team and guide clinicians and pathologists. Online supplemental material is available for this article. ©RSNA, 2020 See discussion on this article by Luna (pp 1627-1630).

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Year:  2020        PMID: 33001791     DOI: 10.1148/rg.2020200042

Source DB:  PubMed          Journal:  Radiographics        ISSN: 0271-5333            Impact factor:   5.333


  3 in total

Review 1.  The Next Paradigm Shift in the Management of Clear Cell Renal Cancer: Radiogenomics-Definition, Current Advances, and Future Directions.

Authors:  Nikhil Gopal; Pouria Yazdian Anari; Evrim Turkbey; Elizabeth C Jones; Ashkan A Malayeri
Journal:  Cancers (Basel)       Date:  2022-02-04       Impact factor: 6.639

Review 2.  Using Quantitative Imaging for Personalized Medicine in Pancreatic Cancer: A Review of Radiomics and Deep Learning Applications.

Authors:  Kiersten Preuss; Nate Thach; Xiaoying Liang; Michael Baine; Justin Chen; Chi Zhang; Huijing Du; Hongfeng Yu; Chi Lin; Michael A Hollingsworth; Dandan Zheng
Journal:  Cancers (Basel)       Date:  2022-03-24       Impact factor: 6.639

Review 3.  HCC: role of pre- and post-treatment tumor biology in driving adverse outcomes and rare responses to therapy.

Authors:  Sandeep Arora; Roberta Catania; Amir Borhani; Natally Horvat; Kathryn Fowler; Carla Harmath
Journal:  Abdom Radiol (NY)       Date:  2021-06-30
  3 in total

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