Circulating Tumor DNA as a Cancer Biomarker: An Overview of Biological Features and Factors That may Impact on ctDNA Analysis

Cancer cells release nucleic acids, freely or associated with other structures such as vesicles into body fluids, including blood. Among these nucleic acids, circulating tumor DNA (ctDNA) has emerged as a minimally invasive biomarker for tumor molecular profiling. However, certain biological characteristics of ctDNA are still unknown. Here, we provide an overview of the current knowledge about ctDNA biological features, including size and structure as well as the mechanisms of ctDNA shedding and clearance, and the physio-pathological factors that determine ctDNA levels. A better understanding of ctDNA biology is essential for the development of new methods that enable the analysis of ctDNA.

Clinical Utility of Liquid Biopsy-Based Actionable Mutations Detected via ddPCR

Cancer is one of the leading causes of death worldwide and remains a major public health challenge. The introduction of more sensitive and powerful technologies has permitted the appearance of new tumor-specific molecular aberrations with a significant cancer management improvement. Therefore, molecular pathology profiling has become fundamental not only to guide tumor diagnosis and prognosis but also to assist with therapeutic decisions in daily practice. Although tumor biopsies continue to be mandatory in cancer diagnosis and classification, several studies have demonstrated that liquid biopsies could be used as a potential tool for the detection of cancer-specific biomarkers. One of the main advantages is that circulating free DNA (cfDNA) provides information about intra-tumoral heterogeneity, reflecting dynamic changes in tumor burden. This minimally invasive tool has become an accurate and reliable instrument for monitoring cancer genetics. However, implementing liquid biopsies across the clinical practice is still ongoing. The main challenge is to detect genomic alterations at low allele fractions. Droplet digital PCR (ddPCR) is a powerful approach that can overcome this issue due to its high sensitivity and specificity. Here we explore the real-world clinical utility of the liquid biopsy ddPCR assays in the most diagnosed cancer subtypes.

A comprehensive database for integrated analysis of omics data in autoimmune diseases

BACKGROUND

Autoimmune diseases are heterogeneous pathologies with difficult diagnosis and few therapeutic options. In the last decade, several omics studies have provided significant insights into the molecular mechanisms of these diseases. Nevertheless, data from different cohorts and pathologies are stored independently in public repositories and a unified resource is imperative to assist researchers in this field.

RESULTS

Here, we present Autoimmune Diseases Explorer ( https://adex.genyo.es ), a database that integrates 82 curated transcriptomics and methylation studies covering 5609 samples for some of the most common autoimmune diseases. The database provides, in an easy-to-use environment, advanced data analysis and statistical methods for exploring omics datasets, including meta-analysis, differential expression or pathway analysis.

CONCLUSIONS

This is the first omics database focused on autoimmune diseases. This resource incorporates homogeneously processed data to facilitate integrative analyses among studies.

NGS-based liquid biopsy profiling identifies mechanisms of resistance to ALK inhibitors: a step toward personalized NSCLC treatment

Despite impressive and durable responses, nonsmall cell lung cancer (NSCLC) patients treated with anaplastic lymphoma kinase (ALK) inhibitors (ALK-Is) ultimately progress due to development of resistance. Here, we have evaluated the clinical utility of circulating tumor DNA (ctDNA) profiling by next-generation sequencing (NGS) upon disease progression. We collected 26 plasma and two cerebrospinal fluid samples from 24 advanced ALK-positive NSCLC patients at disease progression to an ALK-I. These samples were analyzed by NGS and digital PCR. A tool to retrieve variants at the ALK locus was developed (VALK tool). We identified at least one resistance mutation in the ALK locus in ten (38.5%) plasma samples; the G1269A and G1202R mutations were the most prevalent among patients progressing to first- and second-generation ALK-Is, respectively. Overall, 61 somatic mutations were detected in 14 genes: TP53, ALK, PIK3CA, SMAD4, MAP2K1 (MEK1), FGFR2, FGFR3, BRAF, EGFR, IDH2, MYC, MET, CCND3, and CCND1. Specifically, a deletion in exon 19 in EGFR, a non-V600 BRAF mutation (G466V), and the F129L mutation in MAP2K1 were identified in four patients who showed no objective survival benefit from ALK-Is. Potential ALK-I-resistance mutations were also found in PIK3CA and IDH2. Finally, a c-MYC gain, along with a loss of CCND1 and FGFR3, was detected in a patient progressing on a first-line treatment with crizotinib. We conclude that NGS analysis of liquid biopsies upon disease progression identified different putative ALK-I-resistance mutations in most cases and could be a valuable approach for therapy decision making.

Potential Therapeutic Effects of the Neural Stem Cell-Targeting Antibody Nilo1 in Patient-Derived Glioblastoma Stem Cells

Glioblastoma (GBM) is the most devastating and least treatable brain tumor with median survival <15 months and extremely high recurrence rates. Promising results of immune checkpoint blockade obtained from pre-clinical studies in mice did not translate to clinic, and new strategies are urgently needed, particularly those targeting GBM stem cells (GSCs) that are held responsible for drug resistance and tumor recurrence. Patient-derived GSC cultures are critical for finding effective brain tumor therapies. Here, we investigated the ability of the recently described monoclonal antibody Nilo1 to specifically recognize GSCs isolated from GBM surgical samples. We employed five patient-derived GSC cultures with different stemness marker expression and differentiation potential, able to recapitulate original tumors when xenotransplanted in vivo. To answer whether Nilo1 has any functional effects in patient-derived GSCs lines, we treated the cells with Nilo1 in vitro and analyzed cell proliferation, cell cycle, apoptosis, sphere formation, as well as the expression of stem vs. differentiation markers. All tested GSCs stained positively for Nilo1, and the ability of Nilo1 to recognize GSCs strongly relied on their stem-like phenotype. Our results showed that a subset of patient-derived GSCs were sensitive to Nilo1 treatment. In three GSC lines Nilo1 triggered differentiation accompanied by the induction of p21. Most strikingly, in one GSC line Nilo1 completely abrogated self-renewal and led to Bax-associated apoptosis. Our data suggest that Nilo1 targets a molecule functionally relevant for stemness maintenance and pinpoint Nilo1 as a novel antibody-based therapeutical strategy to be used either alone or in combination with cytotoxic drugs for GSC targeting. Further pre-clinical studies are needed to validate the effectiveness of GSC-specific Nilo1 targeting in vivo.

mCSEA: detecting subtle differentially methylated regions

MOTIVATION

The identification of differentially methylated regions (DMRs) among phenotypes is one of the main goals of epigenetic analysis. Although there are several methods developed to detect DMRs, most of them are focused on detecting relatively large differences in methylation levels and fail to detect moderate, but consistent, methylation changes that might be associated to complex disorders.

RESULTS

We present mCSEA, an R package that implements a Gene Set Enrichment Analysis method to identify DMRs from Illumina450K and EPIC array data. It is especially useful for detecting subtle, but consistent, methylation differences in complex phenotypes. mCSEA also implements functions to integrate gene expression data and to detect genes with significant correlations among methylation and gene expression patterns. Using simulated datasets we show that mCSEA outperforms other tools in detecting DMRs. In addition, we applied mCSEA to a previously published dataset of sibling pairs discordant for intrauterine hyperglycemia exposure. We found several differentially methylated promoters in genes related to metabolic disorders like obesity and diabetes, demonstrating the potential of mCSEA to identify DMRs not detected by other methods.

AVAILABILITY AND IMPLEMENTATION

mCSEA is freely available from the Bioconductor repository.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

ImaGEO: integrative gene expression meta-analysis from GEO database

SUMMARY

The Gene Expression Omnibus (GEO) database provides an invaluable resource of publicly available gene expression data that can be integrated and analyzed to derive new hypothesis and knowledge. In this context, gene expression meta-analysis (geMAs) is increasingly used in several fields to improve study reproducibility and discovering robust biomarkers. Nevertheless, integrating data is not straightforward without bioinformatics expertise. Here, we present ImaGEO, a web tool for geMAs that implements a complete and comprehensive meta-analysis workflow starting from GEO dataset identifiers. The application integrates GEO datasets, applies different meta-analysis techniques and provides functional analysis results in an easy-to-use environment. ImaGEO is a powerful and useful resource that allows researchers to integrate and perform meta-analysis of GEO datasets to lead robust findings for biomarker discovery studies.

AVAILABILITY AND IMPLEMENTATION

ImaGEO is accessible at http://bioinfo.genyo.es/imageo/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Polyethylene glycol improves current methods for circulating extracellular vesicle-derived DNA isolation

Background

Extracellular vesicles (EVs) are small membrane-bound vesicles which play an important role in cell-to-cell communication. Their molecular cargo analysis is presented as a new source for biomarker detection, and it might provide an alternative to traditional solid biopsies. However, the most effective approach for EV isolation is not yet well established.

Results

Here, we study the efficiency of the most common EV isolation methods-ultracentrifugation, Polyethlyene glycol and two commercial kits, Exoquick^® and PureExo^®. We isolated circulating EVs from the bloodstream of healthy donors, characterized the size and yield of EVs and analyzed their protein profiles and concentration. Moreover, we have used for the first time Digital-PCR to identify and detect specific gDNA sequences, which has several implications for diagnostic and monitoring many types of diseases.

Conclusions

Our findings present Polyethylene glycol precipitation as the most feasible and less cost-consuming EV isolation technique.

Multiple immunofluorescence assay identifies upregulation of Active β-catenin in prostate cancer

Objectives

To apply a systems pathology-based approach to the quantification of nuclear Active β-catenin and human leukocyte antigen class I, and assess the biomarker involvement in a cohort of prostate tumor patients.

Results

The systems pathology approach applied allows a precise quantification of the marker expression in the different cell compartments as well as the determination of the areas that coexpress two markers. Our data shows that the accumulation of β-catenin in the nuclear compartment is significantly decreased in the adjacent normal areas when compared to tumor of the same patients (p < 0.001). In conclusion, the application of this novel multiple immunofluorescence assay demonstrates that the upregulation of Active β-catenin is a relatively common feature of prostate tumor development, and further supports the activation of the Wnt/β-catenin pathway in prostate cancer progression.

Electronic supplementary material

The online version of this article (10.1186/s13104-019-4100-z) contains supplementary material, which is available to authorized users.