AI Article Synopsis

  • Mass-spectrometry analyses have identified potential protein biomarkers for epithelial ovarian cancer (EOC) that need further validation for clinical application.
  • The Deep MALDI method created a blood-based proteomic classifier that successfully categorized EOC patients based on survival outcomes, revealing an age-dependent prognostic performance.
  • The findings indicate that systemic conditions reflected in proteomic patterns, including complement activation and inflammatory responses, can impact survival and therapy effectiveness in ovarian cancer patients, suggesting their consideration in treatment planning.

Article Abstract

Mass-spectrometry-based analyses have identified a variety of candidate protein biomarkers that might be crucial for epithelial ovarian cancer (EOC) development and therapy response. Comprehensive validation studies of the biological and clinical implications of proteomics are needed to advance them toward clinical use. Using the Deep MALDI method of mass spectrometry, we developed and independently validated (development cohort: = 199, validation cohort: = 135) a blood-based proteomic classifier, stratifying EOC patients into good and poor survival groups. We also determined an age dependency of the prognostic performance of this classifier, and our protein set enrichment analysis showed that the good and poor proteomic phenotypes were associated with, respectively, lower and higher levels of complement activation, inflammatory response, and acute phase reactants. This work highlights that, just like molecular markers of the tumor itself, the systemic condition of a patient (partly reflected in proteomic patterns) also influences survival and therapy response in a subset of ovarian cancer patients and could therefore be integrated into future processes of therapy planning.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7564837PMC
http://dx.doi.org/10.3390/cancers12092519DOI Listing

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