4.7 Article

Individualised proteome profiling of human endometrial tumours improves detection of new prognostic markers

Journal

BRITISH JOURNAL OF CANCER
Volume 109, Issue 3, Pages 704-713

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/bjc.2013.359

Keywords

endometrial cancer; proteomics; systemic analysis; personalised diagnostics

Categories

Funding

  1. Swedish Cancer Research foundation
  2. Swedish Research Council
  3. Radiumhemmet Research Foundation
  4. SI
  5. Personalised Cancer Medicine Unit-KI
  6. Erasmus program KI-UWM
  7. EurocanPlatform
  8. Stockholm County Council
  9. Karolinska Institutet (ALF) [510 222]
  10. Swedish Labor Market Insurance

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Background: The individual features of tumours are often disregarded in cohort studies. As these features may represent a source for individualised cancer treatment, it is important to develop a novel approach for their assessment. Methods: We used proteomics, systems biology, and immunohistochemistry to explore protein expression in human endometrial tumours, to identify deregulated regulatory mechanisms, and to validate observed changes in protein expression using tissue microarrays. Results: Compared with the evaluation of common tumour features, the evaluation of individual tumour features gave a more comprehensive and detailed overview of the regulatory processes in endometrial tumours. Systemic analysis of the individual proteome profiles showed that endometrial tumours employed different proteins to regulate similar functions. Comparison of our data with publicly available data sets of molecular profiling of human endometrial tumours confirmed that individual tumour features are not simply irrelevant individual variations, but are indeed important in endometrial tumorigenesis. Validation through tissue microarray investigation of MST1 and PKN1 proteins confirmed the usefulness of this approach, and suggested that MST1 and PKN1 may be considered as predictive biomarkers of endometrial cancer. Conclusion: We show that individualised profiling of endometrial tumours may deliver better insights into a tumour's physiology, thereby giving a better prediction of tumour development. Individual tumour features may also be used to tailor cancer treatment.

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