Proteomics advances for precision therapy in ovarian cancer

ABSTRACT

Introduction: Due to the relatively low mutation rate and high frequency of copy number variation, finding actionable genetic drivers of high-grade serous carcinoma (HGSC) is a challenging task. Furthermore, emerging studies show that genetic alterations are frequently poorly represented at the protein level adding a layer of complexity. With improvements in large-scale proteomic technologies, proteomics studies have the potential to provide robust analysis of the pathways driving high HGSC behavior.

Areas covered: This review summarizes recent large-scale proteomics findings across adequately sized ovarian cancer sample sets. Key words combined with ‘ovarian cancer’ including ‘proteomics’, ‘proteogenomic’, ‘reverse-phase protein array’, ‘mass spectrometry’, and ‘adaptive response’, were used to search PubMed.

Expert opinion: Proteomics analysis of HGSC as well as their adaptive responses to therapy can uncover new therapeutic liabilities, which can reduce the emergence of drug resistance and potentially improve patient outcomes. There is a pressing need to better understand how the genomic and epigenomic heterogeneity intrinsic to ovarian cancer is reflected at the protein level and how this information could be used to improve patient outcomes.

KEYWORDS:

• Ovarian cancer
• proteomics
• adaptive responses

Article highlights

• HGSC presents with low mutation rate and high frequency of copy number variation, which makes it difficult to identify reliable therapeutics targets.

• Discrepancy between DNA, RNA, and Protein levels has been observed in ovarian cancer likely due to post-transcriptional or post-translational modification as well as effects of miRNA and lncRNA on RNA stability and translation.

• Proteomics studies using reverse-phase protein arrays have allowed the identification of proteins associated with patient outcome, chemoresistance and progression of ovarian cancer.

• The Clinical Proteomic Tumor Analysis Consortium CPTAC group used mass spectrometry to subclassify ovarian cancer and identify signature of chromosomal instability (CIN) and homologous recombination defect (HRD)

• Proteomics can uncover how ovarian cancer cells and the tumor ecosystem adapts to therapy and has the potential to improve patient outcomes by development and implementation of effective drug combinations.

Declaration of interest

G.B. Mills is an advisory board member for AstraZeneca, ImmunoMET, Ionis, Nuevolution, PDX bio, Signalchem, Symphogen, and Tarveda, holds stock options for Catena Pharmaceuticals, ImmunoMet, SignalChem, Spindle Top Ventures and Tarveda, travel support from Chrysallis Bio, and has licensed technology to Nanostring and Myriad Genetics. L. Campbell is a consultant for Quantitative Imaging System.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

G.B. Mills is supported by a kind gift from the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation, the Ovarian Cancer Research Foundation, The Breast Cancer Research Foundation, The Komen Foundation SAC110052, and U.S. Department of Health and Human Services, National Institutes of Health, National Cancer Institute grants: [CA217685, CA217842, and CA098258]; M. Labrie is supported by the Ovarian Cancer Research Alliance and and Ruth and Steve Anderson, in honor of Shae Anderson Gerlinger. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.