Clinical relevance of cytoskeleton associated proteins for ovarian cancer


PURPOSE: Ovarian cancer has a high mortality rate and up to now no reliable molecular prognostic biomarkers have been established. During malignant progression, the cytoskeleton is strongly altered. Hence we analyzed if expression of certain cytoskeleton-associated proteins is correlated with clinical outcome of ovarian cancer patients.

METHODS: First, in silico analysis was performed using the cancer genome atlas (TCGA), the human expression atlas and Pubmed. Selected candidates were validated on 270 ovarian cancer patients by qRT-PCR and/or by western blotting.

RESULTS: In silico analysis revealed that mRNAs of 214 cytoskeleton-associated proteins are detectable in ovarian cancer tissue. Among these, we selected 17 proteins that participate in cancer disease progression and cytoskeleton modulation: KIF14, KIF20A, KIF18A, ASPM, CEP55, DLGAP5, MAP9, EB1, KATNA1, DIAPH1, ANLN, SCIN, CCDC88A, FSCN1, GSN, VASP and CDC42. The first ten candidates interact with microtubules (MTs) and the others bind to actin filaments. Validation on clinical samples of ovarian cancer patients revealed that the expression levels of DIAPH1, EB1, KATNA1, KIF14 and KIF18A significantly correlated with clinical and histological parameters of ovarian cancer. High DIAPH1, EB1, KATNA1 and KIF14 protein levels were associated with increased overall survival (OAS) of ovarian cancer patients, while high DIAPH1 and EB1 protein levels were also associated with low differentiation of respective tumors (G2/3). Moreover, DIAPH1 was the only protein, whose expression significantly correlated with increased recurrence-free interval (RFI).

CONCLUSION: Mainly the expression levels of the MT-associated proteins analyzed in this study, correlated with prolonged survival of ovarian cancer patients. From > 200 genes initially considered, 17 cytoskeletal proteins are involved in cancer progression according to the literature. Among these, four proteins significantly correlated with improved survival of ovarian cancer patients.

Bibliographical data

Original languageEnglish
Publication statusPublished - 11.2018
PubMed 30094535