Targeted proteomics identifies liquid-biopsy signatures for extracapsular prostate cancer

Abstract

Biomarkers are rapidly gaining importance in personalized medicine. Although numerous molecular signatures have been developed over the past decade, there is a lack of overlap and many biomarkers fail to validate in independent patient cohorts and hence are not useful for clinical application. For these reasons, identification of novel and robust biomarkers remains a formidable challenge. We combine targeted proteomics with computational biology to discover robust proteomic signatures for prostate cancer. Quantitative proteomics conducted in expressed prostatic secretions from men with extraprostatic and organ-confined prostate cancers identified 133 differentially expressed proteins. Using synthetic peptides, we evaluate them by targeted proteomics in a 74-patient cohort of expressed prostatic secretions in urine. We quantify a panel of 34 candidates in an independent 207-patient cohort. We apply machine-learning approaches to develop clinical predictive models for prostate cancer diagnosis and prognosis. Our results demonstrate that computationally guided proteomics can discover highly accurate non-invasive biomarkers.

Integrating biomarkers across omic platforms: an approach to improve stratification of patients with indolent and aggressive prostate cancer

“…Of the proteins that had two peptides identified the majority had coefficients in agreement between the two peptides; for example, Apolipoprotein E had coefficients of À6.23E-05 and À9.73E-06 for significant disease VQAAVGT-SAAPVPSDNH and WVQTLSEQVQEELLSSQVT-QELR, respectively. However, complement factor H-related protein 2 had coefficients of 1.17E+00 and À3.71E-02 with opposing signs for ITCAEEGWSPTPK and TGDIVEFVCK, respectively; this could be due to the presence of multiple proteoforms, post-translational modifications, variations in proteolytic digestion efficiencies or inaccurate quantification as has previously been described by Kim et al (2016) and would require additional study.…”

“…(2011) have identified a five serum glycoprotein biomarkers signatures for predicting tissue PTEN status and diagnosis and grading that predicted patients with a Gleason score < 7 or > 7 with an AUC value of 0.78. A urine proteomic peptide panel assessed by targeted proteomics identified proteins to predict pT3 disease before radical prostatectomy with an AUC of 0.74 compared to PSA alone of 0.66 (Kim et al ., 2016). Additional studies by our group have identified a serum protein panel predictive of increased stage of PCa with AUC 0.74 (Fan et al ., 2011).…”

“…However, complement factor H‐related protein 2 had coefficients of 1.17E+00 and −3.71E‐02 with opposing signs for ITCAEEGWSPTPK and TGDIVEFVCK, respectively; this could be due to the presence of multiple proteoforms, post‐translational modifications, variations in proteolytic digestion efficiencies or inaccurate quantification as has previously been described by Kim et al . (2016) and would require additional study.…”

Multi-omics biomarker pipeline reveals elevated levels of protein-glutamine gamma-glutamyltransferase 4 in seminal plasma of prostate cancer patients

“…TGM4 was previously suggested as a prostate cancer biomarker, but results were inconsistent and revealed either significant over-expression 65 or under-expression [66][67][68][69] of TGM4 in PCa versus benign disease, or inconclusive results with the opposite directions based on different assays 70 . TGM4 was found down-regulated 1.7-fold in urinary extracellular vesicles of PCa and had AUC 0.58 to diagnose PCa on biopsy 66 .…”

Mass spectrometry-based proteomics in cancer research

“…Nowadays, liquid biopsy is actively investigated for disease monitoring, and the analysis of key metabolites (molecules less than 1 kDa) in body fluids has become an important approach to improve the risk analysis and early diagnosis of disease [6,7]. For example, Sequeiros et al identified that ADSV-TGM4 combination in urinary extracellular vesicles could classify benign and prostate cancer patients with high sensitivity and specificity [8].…”