Proteomics

Dataset Information

0

Multi-level proteomics identifies CT45 as a chemosensitivity mediator and immunotherapy target in ovarian cancer


ABSTRACT: Most high-grade serous ovarian cancer (HGSOC) patients develop resistance to platinum-based chemotherapy and recur, but 15% remain disease-free over a decade. To discover drivers of long-term survival, we quantitatively analyzed the proteomes of platinum resistant and sensitive HGSOC patients from minute amounts of formalin-fixed, paraffin-embedded tumors. This revealed cancer/testis antigen 45 (CT45) as an independent prognostic factor associated with a doubling of disease-free survival in advanced stage HGSOC. Phospho- and interaction proteomics tied CT45 to DNA damage pathways through direct interaction with the PP4 phosphatase complex. In vitro, CT45 regulated PP4 activity and its high expression led to increased DNA damage and platinum sensitivity. CT45-derived HLA class I peptides, identified by immunopeptidomics, activate patient-derived cytotoxic T cells and promote tumor cell killing. This study highlights the power of clinical cancer proteomics to identify targets for chemo- and immunotherapy and illuminate their biological roles.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Epithelial Cell, Epithelial Ovarian Cancer Cell

DISEASE(S): Malignant Neoplasm Of Ovary

SUBMITTER: Mario Oroshi  

LAB HEAD: Matthias Mann

PROVIDER: PXD010372 | Pride | 2020-04-19

REPOSITORIES: Pride

altmetric image

Publications


Most high-grade serous ovarian cancer (HGSOC) patients develop resistance to platinum-based chemotherapy and recur, but 15% remain disease free over a decade. To discover drivers of long-term survival, we quantitatively analyzed the proteomes of platinum-resistant and -sensitive HGSOC patients from minute amounts of formalin-fixed, paraffin-embedded tumors. This revealed cancer/testis antigen 45 (CT45) as an independent prognostic factor associated with a doubling of disease-free survival in adv  ...[more]

Similar Datasets

2015-11-26 | E-GEOD-75414 | biostudies-arrayexpress
2022-01-04 | GSE163152 | GEO
2021-03-27 | GSE149146 | GEO
2021-03-27 | GSE149145 | GEO
2021-03-27 | GSE147645 | GEO
2023-06-21 | GSE227100 | GEO
2022-02-02 | GSE168225 | GEO
2022-02-02 | GSE169617 | GEO
2019-07-01 | GSE129098 | GEO
2019-07-01 | GSE129097 | GEO