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High-throughput assessment of the antibody profile in ovarian cancer ascitic fluids

Antony F.
•
Deantonio C.
•
Cotella D.
altro
Sblattero D.
2019
  • journal article

Periodico
ONCOIMMUNOLOGY
Abstract
The identification of effective biomarkers for early diagnosis, prognosis, and response to treatments remains a challenge in ovarian cancer (OC) research. Here, we present an unbiased high-throughput approach to profile ascitic fluid autoantibodies in order to obtain a tumor-specific antigen signature in OC. We first reported the reactivity of immunoglobulins (Igs) purified from OC patient ascites towards two different OC cell lines. Using a discovery set of Igs, we selected tumor-specific antigens from a phage display cDNA library. After biopanning, 700 proteins were expressed as fusion protein and used in protein array to enable large-scale immunoscreening with independent sets of cancer and noncancerous control. Finally, the selected antigens were validated by ELISA. The initial screening identified eight antigenic clones: CREB3, MRPL46, EXOSC10, BCOR, HMGN2, HIP1R, OLFM4, and KIAA1755. These antigens were all validated by ELISA in a study involving ascitic Igs from 153 patients (69 with OC, 34 with other cancers and 50 without cancer), with CREB3 showing the highest sensitivity (86.95%) and specificity (98%). Notably, we were able to identify an association between the tumor-associated (TA) antibody response and the response to a first-line tumor treatment (platinum-based chemotherapy). A stronger association was found by combining three antigens (BCOR, CREB3, and MRLP46) as a single antibody signature. Measurement of an ascitic fluid antibody response to multiple TA antigens may aid in the identification of new prognostic signatures in OC patients and shift attention to new potentially relevant targets.
DOI
10.1080/2162402X.2019.1614856
WOS
WOS:000482257800002
Archivio
http://hdl.handle.net/11368/2962055
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85067045897
https://www.tandfonline.com/doi/full/10.1080/2162402X.2019.1614856
Diritti
open access
license:copyright editore
license:digital rights management non definito
FVG url
https://arts.units.it/request-item?handle=11368/2962055
Soggetti
  • ascite

  • biomarker

  • Ovarian cancer

  • protein microarray

  • tumor-associated anti...

Web of Science© citazioni
21
Data di acquisizione
Mar 28, 2024
Visualizzazioni
2
Data di acquisizione
Apr 19, 2024
Vedi dettagli
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