SwePub
Sök i LIBRIS databas

  Extended search

WFRF:(Gatto Francesco 1987)
 

Search: WFRF:(Gatto Francesco 1987) > (2020) > Pan-cancer analysis...

Pan-cancer analysis of the metabolic reaction network

Gatto, Francesco, 1987 (author)
Chalmers tekniska högskola,Chalmers University of Technology
Ferreira, Raphael, 1990 (author)
Chalmers tekniska högskola,Chalmers University of Technology
Nielsen, Jens B, 1962 (author)
BioInnovation Institute (BII),Chalmers tekniska högskola,Chalmers University of Technology
 (creator_code:org_t)
Elsevier BV, 2020
2020
English.
In: Metabolic Engineering. - : Elsevier BV. - 1096-7176 .- 1096-7184. ; 57, s. 51-62
  • Journal article (peer-reviewed)
Abstract Subject headings
Close  
  • Metabolic reprogramming is considered a hallmark of malignant transformation. However, it is not clear whether the network of metabolic reactions expressed by cancers of different origin differ from each other or from normal human tissues. In this study, we reconstructed functional and connected genome-scale metabolic models for 917 primary tumor samples across 13 types based on the probability of expression for 3765 reference metabolic genes in the sample. This network-centric approach revealed that tumor metabolic networks are largely similar in terms of accounted reactions, despite diversity in the expression of the associated genes. On average, each network contained 4721 reactions, of which 74% were core reactions (present in >95% of all models). Whilst 99.3% of the core reactions were classified as housekeeping also in normal tissues, we identified reactions catalyzed by ARG2, RHAG, SLC6 and SLC16 family gene members, and PTGS1 and PTGS2 as core exclusively in cancer. These findings were subsequently replicated in an independent validation set of 3388 genome-scale metabolic models. The remaining 26% of the reactions were contextual reactions. Their inclusion was dependent in one case (GLS2) on the absence of TP53 mutations and in 94.6% of cases on differences in cancer types. This dependency largely resembled differences in expression patterns in the corresponding normal tissues, with some exceptions like the presence of the NANP-encoded reaction in tumors not from the female reproductive system or of the SLC5A9-encoded reaction in kidney-pancreatic-colorectal tumors. In conclusion, tumors expressed a metabolic network virtually overlapping the matched normal tissues, raising the possibility that metabolic reprogramming simply reflects cancer cell plasticity to adapt to varying conditions thanks to redundancy and complexity of the underlying metabolic networks. At the same time, the here uncovered exceptions represent a resource to identify selective liabilities of tumor metabolism.

Subject headings

NATURVETENSKAP  -- Biologi -- Bioinformatik och systembiologi (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Cancer och onkologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Cancer and Oncology (hsv//eng)
NATURVETENSKAP  -- Biologi -- Genetik (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences -- Genetics (hsv//eng)

Keyword

Cancer metabolism
Genome-scale metabolic modeling

Publication and Content Type

art (subject category)
ref (subject category)

Find in a library

To the university's database

Search outside SwePub

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Close

Copy and save the link in order to return to this view