Chronic kidney disease (CKD) affects 8 to 16% people worldwide, with an increasing incidence and prevalence of end-stage kidney disease (ESKD). The effective management of CKD is confounded by the inability to identify patients at high risk of progression while in early stages of CKD. To address this challenge, a renal biopsy transcriptome-driven approach was applied to develop noninvasive prognostic biomarkers for CKD progression. Expression of intrarenal transcripts was correlated with the baseline estimated glomerular filtration rate (eGFR) in 261 patients. Proteins encoded by eGFR-associated transcripts were tested in urine for association with renal tissue injury and baseline eGFR. The ability to predict CKD progression, defined as the composite of ESKD or 40% reduction of baseline eGFR, was then determined in three independent CKD cohorts. A panel of intrarenal transcripts, including epidermal growth factor (EGF), a tubule-specific protein critical for cell differentiation and regeneration, predicted eGFR. The amount of EGF protein in urine (uEGF) showed significant correlation (P < 0.001) with intrarenal EGF mRNA, interstitial fibrosis/tubular atrophy, eGFR, and rate of eGFR loss. Prediction of the composite renal end point by age, gender, eGFR, and albuminuria was significantly (P < 0.001) improved by addition of uEGF, with an increase of the C-statistic from 0.75 to 0.87. Outcome predictions were replicated in two independent CKD cohorts. Our approach identified uEGF as an independent risk predictor of CKD progression. Addition of uEGF to standard clinical parameters improved the prediction of disease events in diverse CKD populations with a wide spectrum of causes and stages.

Antibody-based proteomics play a very important role in biomarker discovery and validation, facilitating the high-throughput evaluation of candidate markers. Most proteomics-driven discovery is nowadays based on the use of MS. MS has many advantages, including its suitability for hypothesis-free biomarker discovery, since information on protein content of a sample is not required prior to analysis. However, MS presents one main caveat which is the limited sensitivity in complex samples, especially for body fluids, where protein expression covers a huge dynamic range. Antibody-based technologies remain the main solution to address this challenge since they reach higher sensitivity. In this article, we review the benefits and limitations of antibody-based proteomics in preclinical and clinical biomarker research for discovery and validation in body fluids and tissue. The combination of antibodies and MS, utilizing the best of both worlds, opens new avenues in biomarker research.

One major materno‐fetal interface in the human placenta is constituted by the syncytiotrophoblast, in contact with maternal blood of the intervillous space, which derives from differentiation and fusion of the villous cytotrophoblast (vct). In the present work, we purified vct from term placenta by depleting HLA class I‐ and class II‐positive cells. We found by RT‐PCR that both soluble intron 4‐retaining HLA‐G1 (sHLA‐G1) and HLA‐G2 isoforms were transcribed in purified vct. Using different HLA‐G‐specific mAb, we demonstrated by intracellular flow cytometry, Western blotting and ELISA, that sHLA‐G1 but no soluble HLA class Ia molecule was secreted by vct. We then purified sHLA‐G1 from vct culture supernatant and found that it exhibited an unusual glycosylation pattern. Finally, we showed that such trophoblast‐derived sHLA‐G1 triggered specific apoptosis of activated CD8+ T cells. Taken together, these results demonstrated that vct did secrete functional sHLA‐G1 in primary culture and suggested that, in vivo, sHLA‐G1 might be an important immunomodulatory molecule controlling the activity of maternal immune effector CD8+ cells circulating in the blood that immerses chorionic villi.

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