Literature DB >> 24706491

Cancer beyond organ and tissue specificity: next-generation-sequencing gene mutation data reveal complex genetic similarities across major cancers.

D Heim1, J Budczies, A Stenzinger, D Treue, P Hufnagl, C Denkert, M Dietel, F Klauschen.   

Abstract

Cancer medicine relies on the paradigm that cancer is an organ- and tissue-specific disease, which is the basis for classifying tumors. With the extensive genomic information now available on tumors it is possible to conduct analyses to reveal common genetic features across cancer types and to explore whether the established anatomy-based tumor classification is actually reflected on the genetic level, which might provide important guides to new therapeutic directions. Here, we have conducted an extensive analysis of the genetic similarity of tumors from 14 major cancer entities using somatic mutation data from 4,796 cases available through The Cancer Genome Atlas (TCGA) based on all available genes as well as different cancer-related gene sets. Our analysis provides a systematic account of the genetic similarity network for major cancer types and shows that in about 43% of the cases on average, tumors of a particular anatomic site are genetically more similar to tumors from different organs and tissues (trans-similarity) than to tumors of the same origin (self-similarity). The observed similarities exist not only for carcinomas from different sites but are also present among neoplasms from different tissue origin, such as melanoma, acute myeloid leukemia, and glioblastoma. The current WHO cancer classification is therefore reflected on the genetic level by only about 57% of the tumors. These results provide a rationale to reconsider organ- and tissue-specificity in cancer and contribute to the discussion about whether personalized therapies targeting specific genetic alterations may be transferred to cancers from other anatomic sites with similar genetic properties.
© 2014 UICC.

Entities:  

Keywords:  WHO cancer classification; cancer genetics; mutational cancer profiling; personalized medicine

Mesh:

Substances:

Year:  2014        PMID: 24706491     DOI: 10.1002/ijc.28882

Source DB:  PubMed          Journal:  Int J Cancer        ISSN: 0020-7136            Impact factor:   7.396


  14 in total

Review 1.  [Mutational tumor profiles beyond organ and tissue specificity: implications for diagnostics and clinical study design].

Authors:  F Klauschen
Journal:  Pathologe       Date:  2014-11       Impact factor: 1.011

2.  Semiconductor-based sequencing of formalin-fixed, paraffin-embedded colorectal cancer samples.

Authors:  Albrecht Stenzinger; Nicole Pfarr; Roland Penzel; Thomas Wolf; Peter Schirmacher; Volker Endris; Wilko Weichert
Journal:  Oncologist       Date:  2015-04-10

3.  Prognostic impact of HER3 based on protein and mRNA expression in high-grade serous ovarian carcinoma.

Authors:  Ulrike Unger; Carsten Denkert; Ioana Braicu; Jalid Sehouli; Manfred Dietel; Sibylle Loibl; Silvia Darb-Esfahani
Journal:  Virchows Arch       Date:  2016-12-02       Impact factor: 4.064

4.  Pan-cancer analysis of the extent and consequences of intratumor heterogeneity.

Authors:  Noemi Andor; Trevor A Graham; Marnix Jansen; Li C Xia; C Athena Aktipis; Claudia Petritsch; Hanlee P Ji; Carlo C Maley
Journal:  Nat Med       Date:  2015-11-30       Impact factor: 53.440

5.  The combinatorial complexity of cancer precision medicine.

Authors:  Frederick Klauschen; Michael Andreeff; Ulrich Keilholz; Manfred Dietel; Albrecht Stenzinger
Journal:  Oncoscience       Date:  2014-07-23

Review 6.  Cancer classification in the genomic era: five contemporary problems.

Authors:  Qingxuan Song; Sofia D Merajver; Jun Z Li
Journal:  Hum Genomics       Date:  2015-10-19       Impact factor: 4.639

7.  Identification of cancer biomarkers of prognostic value using specific gene regulatory networks (GRN): a novel role of RAD51AP1 for ovarian and lung cancers.

Authors:  Dimple Chudasama; Valeria Bo; Marcia Hall; Vladimir Anikin; Jeyarooban Jeyaneethi; Jane Gregory; George Pados; Allan Tucker; Amanda Harvey; Ryan Pink; Emmanouil Karteris
Journal:  Carcinogenesis       Date:  2018-03-08       Impact factor: 4.944

8.  Computational analysis reveals histotype-dependent molecular profile and actionable mutation effects across cancers.

Authors:  Daniel Heim; Grégoire Montavon; Peter Hufnagl; Klaus-Robert Müller; Frederick Klauschen
Journal:  Genome Med       Date:  2018-11-15       Impact factor: 11.117

9.  A multiomics comparison between endometrial cancer and serous ovarian cancer.

Authors:  Hui Zhong; Huiyu Chen; Huahong Qiu; Chen Huang; Zhihui Wu
Journal:  PeerJ       Date:  2020-01-09       Impact factor: 2.984

10.  Detecting heterogeneity in and between breast cancer cell lines.

Authors:  Yang Shen; B U Sebastian Schmidt; Hans Kubitschke; Erik W Morawetz; Benjamin Wolf; Josef A Käs; Wolfgang Losert
Journal:  Cancer Converg       Date:  2020-02-03
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