Literature DB >> 31152602

Histomorphological and molecular profiling: friends not foes! Morpho-molecular analysis reveals agreement between histological and molecular profiling.

Michael Hoberger1, Maximilian von Laffert1, Daniel Heim1, Frederick Klauschen1,2.   

Abstract

AIMS: Whereas current cancer diagnosis largely relies on the well-established organ and tissue typing of tumours, partially complemented by molecular properties, the comprehensive molecular profiling efforts of recent years have stimulated proposals for molecular reclassifications of tumours independently of anatomical origin. Proposals based only on mutational profiles show the least concordance with histotypes, whereas greater concordance is achieved when various genomic and proteomic data are included. METHODS AND
RESULTS: The most comprehensive molecular reclassification of tumours, by Hoadley et  al (Cell, 158, 2014; 929) and Hoadley et  al (Cell, 173, 2018; 291), integrated multi-omics data, and proposes novel molecular tumour classes. To investigate the relationship between the proposed molecular classes and the original histological tumour types, we re-examined the histomorphology of molecularly reclassified cases. Our results show that the claimed molecular reclassification is associated with and explainable by specific histological subtypes in 70% of the reclassified cases.
CONCLUSION: Therefore, in contrast to the proclaimed reclassification and independence of molecular and histological tumour types, our analysis demonstrates that comprehensive molecular profiling, which includes gene expression and methylation as well as proteomic profiling in addition to mutational analyses, is largely consistent with histomorphological tumour properties.
© 2019 John Wiley & Sons Ltd.

Entities:  

Keywords:  clinical pathology; diagnostic molecular pathology; histopathology; morphology; pathology

Mesh:

Year:  2019        PMID: 31152602     DOI: 10.1111/his.13930

Source DB:  PubMed          Journal:  Histopathology        ISSN: 0309-0167            Impact factor:   5.087


  1 in total

Review 1.  Artificial Intelligence in Pathology.

Authors:  Sebastian Försch; Frederick Klauschen; Peter Hufnagl; Wilfried Roth
Journal:  Dtsch Arztebl Int       Date:  2021-03-26       Impact factor: 5.594

  1 in total

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