Discovery and validation of serum glycoprotein biomarkers for high grade serous ovarian cancer

PURPOSE

This study aimed to identify serum glycoprotein biomarkers for early detection of high-grade serous ovarian cancer (HGSOC), the most common and aggressive histotype of ovarian cancer.

EXPERIMENTAL DESIGN

The glycoproteomics pipeline lectin magnetic bead array (LeMBA)-mass spectrometry (MS) was used in age-matched case-control serum samples. Clinical samples collected at diagnosis were divided into discovery (n = 30) and validation (n = 98) sets. We also analysed a set of preclinical sera (n = 30) collected prior to HGSOC diagnosis in the UK Collaborative Trial of Ovarian Cancer Screening.

RESULTS

A 7-lectin LeMBA-MS/MS discovery screen shortlisted 59 candidate proteins and three lectins. Validation analysis using 3-lectin LeMBA-multiple reaction monitoring (MRM) confirmed elevated A1AT, AACT, CO9, HPT and ITIH3 and reduced A2MG, ALS, IBP3 and PON1 glycoforms in HGSOC. The best performing multimarker signature had 87.7% area under the receiver operating curve, 90.7% specificity and 70.4% sensitivity for distinguishing HGSOC from benign and healthy groups. In the preclinical set, CO9, ITIH3 and A2MG glycoforms were altered in samples collected 11.1 ± 5.1 months prior to HGSOC diagnosis, suggesting potential for early detection.

CONCLUSIONS AND CLINICAL RELEVANCE

Our findings provide evidence of candidate early HGSOC serum glycoprotein biomarkers, laying the foundation for further study in larger cohorts.

Identification of Novel Associations and Localization of Signals in Idiopathic Inflammatory Myopathies Using Genome-Wide Imputation

OBJECTIVE

The idiopathic inflammatory myopathies (IIMs) are heterogeneous diseases thought to be initiated by immune activation in genetically predisposed individuals. We imputed variants from the ImmunoChip array using a large reference panel to fine-map associations and identify novel associations in IIM.

METHODS

We analyzed 2,565 Caucasian IIM patient samples collected through the Myositis Genetics Consortium (MYOGEN) and 10,260 ethnically matched control samples. We imputed 1,648,116 variants from the ImmunoChip array using the Haplotype Reference Consortium panel and conducted association analysis on IIM and clinical and serologic subgroups.

RESULTS

The HLA locus was consistently the most significantly associated region. Four non-HLA regions reached genome-wide significance, SDK2 and LINC00924 (both novel) and STAT4 in the whole IIM cohort, with evidence of independent variants in STAT4, and NAB1 in the polymyositis (PM) subgroup. We also found suggestive evidence of association with loci previously associated with other autoimmune rheumatic diseases (TEC and LTBR). We identified more significant associations than those previously reported in IIM for STAT4 and DGKQ in the total cohort, for NAB1 and FAM167A-BLK loci in PM, and for CCR5 in inclusion body myositis. We found enrichment of variants among DNase I hypersensitivity sites and histone marks associated with active transcription within blood cells.

CONCLUSION

We found novel and strong associations in IIM and PM and localized signals to single genes and immune cell types.