Dataset Information

Molecular subtyping of cancer and nomination of kinase candidates for inhibition with phosphoproteomics: Reanalysis of CPTAC ovarian cancer.

ABSTRACT:

Background

Molecular subtyping of cancer aimed to predict patient overall survival (OS) and nominate drug targets for patient treatments is central to precision oncology. Owing to the rapid development of phosphoproteomics, we can now measure thousands of phosphoproteins in human cancer tissues. However, limited studies report how to analyse the complex phosphoproteomic data for cancer subtyping and to nominate druggable kinase candidates.

Findings

In this work, we reanalysed the phosphoproteomic data of high-grade serous ovarian cancer (HGSOC) from the Clinical Proteomic Tumour Analysis Consortium (CPTAC). Our analysis classified HGSOC into 5 major subtypes that were associated with different OS and appeared to be more accurate than that achieved with protein profiling. We provided a workflow to identify 29 kinases whose increased activities in tumours are associated with poor survival. The altered kinase signalling landscape of HGSOC included the PI3K/AKT/mTOR, cell cycle and MAP kinase signalling pathways. We also developed a "patient-specific" hierarchy of clinically actionable kinases and selected kinase inhibitors by considering kinase activation and kinase inhibitor selectivity.

Interpretation

Our study offered a global phosphoproteomics data analysis workflow to aid in cancer molecular subtyping, determining phosphorylation-based cancer hallmarks and facilitating nomination of kinase inhibition in cancer.

SUBMITTER: Tong M

PROVIDER: S-EPMC6412074 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Molecular subtyping of cancer and nomination of kinase candidates for inhibition with phosphoproteomics: Reanalysis of CPTAC ovarian cancer.

Tong Mengsha M Yu Chunyu C Zhan Dongdong D Zhang Ming M Zhen Bei B Zhu Weimin W Wang Yi Y Wu Congying C He Fuchu F Qin Jun J Li Tingting T

EBioMedicine 20181226

<h4>Background</h4>Molecular subtyping of cancer aimed to predict patient overall survival (OS) and nominate drug targets for patient treatments is central to precision oncology. Owing to the rapid development of phosphoproteomics, we can now measure thousands of phosphoproteins in human cancer tissues. However, limited studies report how to analyse the complex phosphoproteomic data for cancer subtyping and to nominate druggable kinase candidates.<h4>Findings</h4>In this work, we reanalysed the ...[more]

PMID: 30594550

Similar Datasets

Project description:Epithelial ovarian cancer is morphologically and clinically heterogeneous. Transcriptional profiling has revealed molecular subtypes (referred to as “C-signatures”) that correlate to biological as well as clinical features. We aimed to determine gene expression differences between malignant, benign and borderline serous ovarian tumors, and to investigate similarities to the intrinsic molecular subtypes of breast cancer. Global gene expression profiling was performed using Illumina's HT12 Bead Arrays and applied to 59 fresh-frozen ovarian tumors. SAM analysis revealed enrichment of cell cycel processes among the malignant tumors, in line with malignant tumors being highly proliferative. The borderline tumors were split between the malignant and benign tumor clusters, indicating that borderline tumors have both malignant and benign features. Furthermore, nearest centroid classification was performed applying previously published gene profiles for the ovarian cancer C-signatures and the intrinsic breast cancer subtypes, respectively, and showed significant correlations between the malignant serous tumors and the highly aggressive C1, C2 and C4 ovarian cancer signatures, and the basal-like breast cancer subtype. The benign and borderline serous tumors together were significantly correlated to the normal-like breast cancer subtype and the ovarian cancer C3 signature. The borderline tumors, on the other hand, correlated significantly to the Luminal A breast cancer subtype. These findings remained when analyzed in a large, independent dataset. The data in this study link the transcriptional profiles of serous ovarian cancer to the intrinsic molecular subtypes of breast cancer, in line with the shared clinical and molecular features between high-grade serous ovarian cancer and basal-like breast cancer, including an aggressive phenotype, frequent TP53 mutations and a high degree of genomic instability, and suggest that biomarkers and targeted therapies may overlap between these subsets of ovarian and breast cancers. Finally, the link between benign and borderline ovarian cancer and luminal breast cancer may indicate endocrine responsiveness in a subset of ovarian cancers. Total RNA obtained from serous ovarian adenocarcinomas, adenomas and borderline tumors. Gene expression profiling using Illumina's HT12 v4 bead arrays. Application of ovarian cancer molecular subtypes and intrinsic breast cancer subtypes using nearest centroid classification. KRAS and BRAF mutation analyses in the malignant and borderline tumors.

Dataset Information

Molecular subtyping of cancer and nomination of kinase candidates for inhibition with phosphoproteomics: Reanalysis of CPTAC ovarian cancer.

Background

Findings

Interpretation

Publications

Molecular subtyping of cancer and nomination of kinase candidates for inhibition with phosphoproteomics: Reanalysis of CPTAC ovarian cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets