Background Current risk models for renal cell carcinoma (RCC) based on clinicopathological factors are sub-optimal in accurately identifying high-risk patients. Here, we perform a head-to-head comparison of previously published DNA methylation markers and propose a potential prognostic model for clear cell RCC (ccRCC). Patients and methods Promoter methylation of PCDH8, BNC1, SCUBE3, GREM1, LAD1, NEFH, RASSF1A, GATA5, SFRP1, CDO1, and NEURL was determined by nested methylation-specific PCR. To identify clinically relevant methylated regions, The Cancer Genome Atlas (TCGA) was used to guide primer design. Formalin-fixed paraffin-embedded (FFPE) tissue samples from 336 non-metastatic ccRCC patients from the prospective Netherlands Cohort Study (NLCS) were used to develop a Cox proportional hazards model using stepwise backward elimination and bootstrapping to correct for optimism. For validation purposes, FFPE ccRCC tissue of 64 patients from the University Hospitals Leuven and a series of 232 cases from The Cancer Genome Atlas (TCGA) were used. Results Methylation of GREM1, GATA5, LAD1, NEFH, NEURL, and SFRP1 was associated with poor ccRCC-specific survival, independent of age, sex, tumor size, TNM stage or tumor grade. Moreover, the association between GREM1, NEFH, and NEURL methylation and outcome was shown to be dependent on the genomic region. A prognostic biomarker model containing GREM1, GATA5, LAD1, NEFH and NEURL methylation in combination with clinicopathological characteristics, performed better compared to the model with clinicopathological characteristics only (clinical model), in both the NLCS and the validation population with a c-statistic of 0.71 versus 0.65 and a c-statistic of 0.95 versus 0.86 consecutively. However, the biomarker model had limited added prognostic value in the TCGA series with a c-statistic of 0.76 versus 0.75 for the clinical model. Conclusion In this study we performed a head-to-head comparison of potential prognostic methylation markers for ccRCC using a novel approach to guide primers design which utilizes the optimal location for measuring DNA methylation. Using this approach, we identified five methylation markers that potentially show prognostic value in addition to currently known clinicopathological factors.

Although population-wide screening programs for several cancer types have been implemented in multiple countries, screening procedures are invasive, time-consuming and often perceived as a burden for patients. Molecular biomarkers measurable in non-invasively collected samples (liquid biopsies) could facilitate screening, as they could have incremental value on early diagnosis of cancer, but could also predict prognosis or monitor treatment response. Although the shift towards biomarkers from liquid biopsies for early cancer detection was initiated some time ago, there are many challenges that hamper the development of such biomarkers. One of these challenges is large-scale validation that requires large prospectively collected biobanks with liquid biopsies. Establishing those biobanks involves several considerations, such as standardization of sample collection, processing and storage within and between biobanks. In this perspective, we will elaborate on several issues that need to be contemplated in biobanking, both in general and for certain specimen types specifically, to be able to facilitate biomarker validation for early detection of cancer.

No abstract

Background: Very few (<0.1%) of DNA methylation biomarkers are eventually translated into clinical practice, even though over 5,000 have been published over the last decades. In an attempt to create an overview of the current evidence on these markers, we performed two systematic reviews on diagnostic DNA methylation biomarkers in liquid biopsies, for colorectal cancer (CRC) and renal cell carcinoma (RCC) (1). Here, we present the evidence of these systematic reviews and provide novel recommendations to improve the current clinical translation of DNA methylation biomarkers. Methods: For CRC, we identified 109 bodily fluid biomarker studies published before January 2019 in PubMed, Embase, Cochrane Library, or Google Scholar. For RCC, we identified 6 liquid biopsy studies up to January 2019 in these databases. Data extraction (study design, patient characteristics, disease stage, tumor location, technical assays, diagnostic measures) was performed on published reports. STARD criteria and Level of Evidence (LoE) were registered to assess reporting quality and strength for clinical translation, and forest plots were generated to summarize diagnostic performance of the biomarkers. Findings: Our systematic literature search revealed multiple issues that hamper the development of DNA methylation biomarkers for RCC and CRC diagnosis, including methodologic and technical heterogeneity and lack of validation or clinical translation. Among the most important issues were a lack of translation from tissue into liquid biopsy; for CRC 88/389 (23%) CRC markers were studied in liquid biopsies, and for RCC these numbers were 15/44 (34%). In addition, results showed a lack of independent validation, with 37/88 (42%) CRC markers and 9/15 (60%) RCC markers in liquid biopsies studied in more than one study or study population. Also, inappropriate marker identification and primer design, lack of true clinical need definition, and low reporting quality were issues that were recognized in our systematic literature searches. These issues all hamper the development of the field, keep the LoE low, and hinder the translation of DNA methylation biomarkers into clinical tests. Interpretation: Our systematic literature searches revealed that major requirements to develop clinically relevant diagnostic DNA methylation markers are often lacking. To avoid the resulting research waste, clinical needs, intended biomarker use, and independent validation should be better considered prior to study design. In addition, improved reporting quality would facilitate meta-analysis, thereby increasing LoE and enabling clinical translation. Reference: 1. Lommen et al. Eur Urol Oncol 2019; https://doi.org/10.1016/j.euo.2019.07.011. Citation Format: Kim Lommen, Zheng Feng, Cary J.G. Oberije, Alouisa J. P. van de Wetering, Selena Odeh, Alexander Koch, Maureen J. B. Aarts, Joep G. van Roermund, Leo J. Schouten, Egbert Oosterwijk, Nathalie Vaes, Ad A. M. Masclee, Beatriz Carvalho, Gerrit A. Meijer, Maurice P. Zeegers, James G. Herman, Vivianne C. Tjan-Heijnen, Veerle Melotte, Manon van Engeland, Kim Smits. Clinical translation of liquid biopsy DNA methylation biomarkers: Lessons from two systematic reviews [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr A62.