ABSTRACT
BACKGROUND: Variation in intercellular methylation patterns can complicate the use of methylation biomarkers for clinical diagnostic applications such as blood-based cancer testing. Here, we describe development and validation of a methylation density binary classification method called EpiClass (available for download at https://github.com/Elnitskilab/EpiClass ) that can be used to predict and optimize the performance of methylation biomarkers, particularly in challenging, heterogeneous samples such as liquid biopsies. This approach is based upon leveraging statistical differences in single-molecule sample methylation density distributions to identify ideal thresholds for sample classification. RESULTS: We developed and tested the classifier using reduced representation bisulfite sequencing (RRBS) data derived from ovarian carcinoma tissue DNA and controls. We used these data to perform in silico simulations using methylation density profiles from individual epiallelic copies of ZNF154, a genomic locus known to be recurrently methylated in numerous cancer types. From these profiles, we predicted the performance of the classifier in liquid biopsies for the detection of epithelial ovarian carcinomas (EOC). In silico analysis indicated that EpiClass could be leveraged to better identify cancer-positive liquid biopsy samples by implementing precise thresholds with respect to methylation density profiles derived from circulating cell-free DNA (cfDNA) analysis. These predictions were confirmed experimentally using DREAMing to perform digital methylation density analysis on a cohort of low volume (1-ml) plasma samples obtained from 26 EOC-positive and 41 cancer-free women. EpiClass performance was then validated in an independent cohort of 24 plasma specimens, derived from a longitudinal study of 8 EOC-positive women, and 12 plasma specimens derived from 12 healthy women, respectively, attaining a sensitivity/specificity of 91.7%/100.0%. Direct comparison of CA-125 measurements with EpiClass demonstrated that EpiClass was able to better identify EOC-positive women than standard CA-125 assessment. Finally, we used independent whole genome bisulfite sequencing (WGBS) datasets to demonstrate that EpiClass can also identify other cancer types as well or better than alternative methylation-based classifiers. CONCLUSIONS: Our results indicate that assessment of intramolecular methylation density distributions calculated from cfDNA facilitates the use of methylation biomarkers for diagnostic applications. Furthermore, we demonstrated that EpiClass analysis of ZNF154 methylation was able to outperform CA-125 in the detection of etiologically diverse ovarian carcinomas, indicating broad utility of ZNF154 for use as a biomarker of ovarian cancer.
Subject(s)
Biomarkers, Tumor/genetics , Carcinoma, Ovarian Epithelial/genetics , Cell-Free Nucleic Acids/blood , Epigenomics/methods , CA-125 Antigen/metabolism , Carcinoma, Ovarian Epithelial/diagnosis , Carcinoma, Ovarian Epithelial/pathology , Case-Control Studies , Cohort Studies , CpG Islands/genetics , DNA Methylation , Female , Genomics/methods , Humans , Kruppel-Like Transcription Factors/genetics , Liquid Biopsy/methods , Longitudinal Studies , Ovarian Neoplasms/pathology , Sensitivity and SpecificityABSTRACT
BACKGROUND: The klotho (KL) gene is an anti-aging gene that has recently been shown to also function as a general tumor suppressor. However, there is currently only limited information regarding the potential molecular signals for regulation of Klotho without identifying precise molecular mechanisms or interactions. METHODS: We performed a mass spectrometry (MS) assay to screen candidate proteins complexed with Klotho derived from immunoprecipitation in human non-small cell lung cancer (NSCLC) cells, and identified Rab8 to be the protein that most prominently interacts with Klotho. We further investigated whether Rab8 can regulate trafficking of Klotho and which process it would modulate using surface biotinylation assay, immunofluorescence and fluorescence ratio microscopy. Furthermore, we explored whether Rab8 is involved in Klotho-mediated function in NSCLC, and verified the results which we found in vivo using xenograft mouse model. FINDINGS: We report discovery of Rab8 as a Klotho-interacting protein that acts as a critical modulator of Klotho surface expression in human NSCLC. In particular, we report that Rab8 is co-localized and associated with Klotho, and Klotho trafficking is regulated by Rab8. Moreover, we found that Rab8 modulates surface levels of Klotho via a post-biosynthetic pathway, as opposed to an endocytic pathway. Furthermore, we demonstrate that Rab8 is involved in Klotho-mediated regulation of cell proliferation, migration, invasiveness, epithelial-mesenchymal transition (EMT), and Wnt-ß-catenin signaling in NSCLC. Additionally, Rab8 overexpression was also found to increase Klotho-mediated inhibition of NSCLC tumorigenesis in vivo. INTERPRETATION: Overall, our findings suggest that Rab8 GTPase can regulate Klotho-mediated inhibition of Wnt signaling activity by modulating translocation of Klotho onto the cell surface, which in turn affects Klotho-mediated inhibition of cell proliferation, migration and invasiveness in NSCLC. These results have important implications for the development of new therapeutic targets, Klotho-related research in the context of NSCLC as well as other areas, and provide a working model for Rab8 function in the context of cancer and cancer biology.
Subject(s)
Carcinoma, Non-Small-Cell Lung/genetics , Carcinoma, Non-Small-Cell Lung/pathology , Disease Progression , Gene Expression Regulation, Neoplastic , Glucuronidase/genetics , Lung Neoplasms/genetics , Lung Neoplasms/pathology , rab GTP-Binding Proteins/metabolism , Animals , Biomarkers, Tumor/metabolism , Carcinogenesis/genetics , Carcinogenesis/pathology , Cell Line, Tumor , Cell Membrane/metabolism , Cell Proliferation , Down-Regulation/genetics , Endocytosis , Epithelial-Mesenchymal Transition/genetics , Glucuronidase/metabolism , Humans , Klotho Proteins , Male , Mice, Inbred BALB C , Mice, Nude , Protein Binding , Survival Analysis , Wnt Signaling Pathway/genetics , rab GTP-Binding Proteins/geneticsABSTRACT
Despite numerous technical hurdles, the realization of true personalized medicine is becoming a progressive reality for the future of patient care. With the development of new techniques and tools to measure the genetic signature of tumors, biomarkers are increasingly being used to detect occult tumors, determine the choice of treatment and predict outcomes. Methylation of CpG islands at the promoter region of genes is a particularly exciting biomarker as it is cancer-specific. Older methods to detect methylation were cumbersome, operator-dependent and required large amounts of DNA. However, a newer technique called methylation on beads has resulted in a more uniform, streamlined and efficient assay. Furthermore, methylation on beads permits the extraction and processing of miniscule amounts of methylated tumor DNA in the peripheral blood. Such a technique may aid in the clinical detection and treatment of cancers in the future.
