Abstract

Transporters of the inner mitochondrial membrane are essential to metabolism. We demonstrate that metabolism as represented by expression of genes encoding SLC25 transporters differentiates human cancers. Tumor to normal tissue expression ratios for clear cell renal cell carcinoma, colon adenocarcinoma, lung adenocarcinoma and breast invasive carcinoma were found to be highly significant. Affinity propagation trained on SLC25 gene expression patterns from 19 human cancer types (6825 TCGA samples) and normal tissues (2322 GTEx samples) was used to generate clusters. They differentiate cancers from normal tissues. They also indicate cancer subtypes with survivals distinct from the total patient population of the cancer type. Probing the kidney, colon, lung, and breast cancer clusters, subtype pairs of cancers were identified with distinct prognoses and differing in expression of protein coding genes from among 2080 metabolic enzymes assayed. We demonstrate that SLC25 expression clusters facilitate the identification of the tissue-of-origin, essential to efficacy of most cancer therapies, of CUPs (cancer-unknown-primary) known to have poor prognoses. Different cancer types within a single cluster have similar metabolic patterns and this raises the possibility that such cancers may respond similarly to existing and new anti-cancer therapies.

Details

Title
Mitochondrial transporter expression patterns distinguish tumor from normal tissue and identify cancer subtypes with different survival and metabolism
Author
Wohlrab, Hartmut 1 ; Signoretti, Sabina 2 ; Rameh, Lucia E. 3 ; DeConti, Derrick K. 4 ; Hansen, Steen H. 5 

 Harvard Medical School, Department of Biological Chemistry and Molecular Pharmacology, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X); Boston Children’s Hospital, GI Cell Biology Research Laboratory, Boston, USA (GRID:grid.2515.3) (ISNI:0000 0004 0378 8438) 
 Brigham and Women’s Hospital, Department of Pathology, Boston, USA (GRID:grid.62560.37) (ISNI:0000 0004 0378 8294); Harvard Medical School, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X) 
 Vanderbilt University, Department of Biochemistry, School of Medicine, Nashville, USA (GRID:grid.152326.1) (ISNI:0000 0001 2264 7217) 
 Harvard T.H. Chan School of Public Health, Quantitative Biomedical Research Center, Department of Biostatistics, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X) 
 Boston Children’s Hospital, GI Cell Biology Research Laboratory, Boston, USA (GRID:grid.2515.3) (ISNI:0000 0004 0378 8438); Harvard Medical School, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2723657513
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.