Johanna Schiewek1, Udo Schumacher2, Tobias Lange2, Simon A Joosse3, Harriet Wikman3, Klaus Pantel3, Marina Mikhaylova4, Matthias Kneussel5, Stefan Linder6, Barbara Schmalfeldt7, Leticia Oliveira-Ferrer7, Sabine Windhorst8. 1. Department of Biochemistry and Signal Transduction, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246, Hamburg, Germany. 2. Institute of Anatomy and Experimental Morphology, University Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246, Hamburg, Germany. 3. Department of Tumor Biology, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246, Hamburg, Germany. 4. DFG Emmy Noether Group 'Neuronal Protein Transport', Center for Molecular Neurobiology, ZMNH, University Medical Center Hamburg-Eppendorf, 20251, Hamburg, Germany. 5. Department of Molecular Neurogenetics, Center for Molecular Neurobiology, ZMNH, University Medical Center Hamburg-Eppendorf, Falkenried 94, 20251, Hamburg, Germany. 6. Institute for Medical Microbiology, Virology and Hygiene, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany. 7. Department of Gynecology, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246, Hamburg, Germany. 8. Department of Biochemistry and Signal Transduction, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246, Hamburg, Germany. s.windhorst@uke.uni-hamburg.de.
Abstract
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.
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 cancerpatients. 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 cancerpatients 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 cancerpatients 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 cancerpatients, 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 cancerpatients. 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 cancerpatients.
Entities:
Keywords:
Actin; Cytoskeleton; Microtubule; Ovarian cancer
Authors: Jacek P Grabowski; Philipp Harter; Florian Heitz; Eric Pujade-Lauraine; Alexander Reuss; Gunnar Kristensen; Isabelle Ray-Coquard; Julia Heitz; Alexander Traut; Jacobus Pfisterer; Andreas du Bois Journal: Gynecol Oncol Date: 2016-01-22 Impact factor: 5.482
Authors: Débora Cabral de Carvalho Corrêa; Indhira Dias Oliveira; Bruna Mascaro Cordeiro; Frederico Adolfo Silva; Maria Teresa de Seixas Alves; Nasjla Saba-Silva; Andrea Maria Capellano; Patrícia Dastoli; Sergio Cavalheiro; Silvia Regina Caminada de Toledo Journal: Childs Nerv Syst Date: 2020-06-26 Impact factor: 1.532
Authors: Sheng Wu; Katja Nitschke; Jakob Heinkele; Cleo-Aron Weis; Thomas Stefan Worst; Markus Eckstein; Stefan Porubsky; Philipp Erben Journal: Cancers (Basel) Date: 2019-11-21 Impact factor: 6.639
Authors: Matthieu P M H Benoit; Ana B Asenjo; Mohammadjavad Paydar; Sabin Dhakal; Benjamin H Kwok; Hernando Sosa Journal: Nat Commun Date: 2021-06-15 Impact factor: 14.919