Current analysis of circulating tumor cells (CTCs) is hindered by sub-optimal sensitivity and specificity of devices or assays as well as lack of capability of characterization of CTCs with clinical biomarkers. Here, we validate a novel technology to enrich and characterize CTCs from blood samples of patients with metastatic breast, prostate and colorectal cancers using a microfluidic chip which is processed by using an automated staining and scanning system from sample preparation to image processing. The Celsee system allowed for the detection of CTCs with apparent high sensitivity and specificity (94% sensitivity and 100% specificity). Moreover, the system facilitated rapid capture of CTCs from blood samples and also allowed for downstream characterization of the captured cells by immunohistochemistry, DNA and mRNA fluorescence in-situ hybridization (FISH). In a subset of patients with prostate cancer we compared the technology with a FDA-approved CTC device, CellSearch and found a higher degree of sensitivity with the Celsee instrument. In conclusion, the integrated Celsee system represents a promising CTC technology for enumeration and molecular characterization.

Purpose: Early detection is essential for treatment plans before onset of metastatic disease. Our purpose was to demonstrate feasibility to detect and monitor estrogen receptor 1 (ESR1) gene mutations at the single circulating tumor cell (CTC) level in metastatic breast cancer (MBC). Experimental Design: We used a CTC molecular characterization approach to investigate heterogeneity of 14 hotspot mutations in ESR1 and their correlation with endocrine resistance. Combining the CellSearch and DEPArray technologies allowed recovery of 71 single CTCs and 12 WBC from 3 ER-positive MBC patients. Forty CTCs and 12 WBC were subjected to whole genome amplification by MALBAC and Sanger sequencing. Results: Among 3 selected patients, 2 had an ESR1 mutation (Y537). One showed two different ESR1 variants in a single CTC and another showed loss of heterozygosity. All mutations were detected in matched cell-free DNA (cfDNA). Furthermore, one had 2 serial blood samples analyzed and showed changes in both cfDNA and CTCs with emergence of mutations in ESR1 (Y537S and T570I), which has not been reported previously. Conclusions: CTCs are easily accessible biomarkers to monitor and better personalize management of patients with previously demonstrated ER-MBC who are progressing on endocrine therapy. We showed that single CTC analysis can yield important information on clonal heterogeneity and can be a source of discovery of novel and potential driver mutations. Finally, we also validate a workflow for liquid biopsy that will facilitate early detection of ESR1 mutations, the emergence of endocrine resistance and the choice of further target therapy. Clin Cancer Res; 23(20); 6086–93. ©2017 AACR.

The availability of blood-based diagnostic testing using a non-invasive technique holds promise for real-time monitoring of disease progression and treatment selection. Circulating tumor cells (CTCs) have been used as a prognostic biomarker for the metastatic breast cancer (MBC). The molecular characterization of CTCs is fundamental to the phenotypic identification of malignant cells and description of the relevant genetic alterations that may change according to disease progression and therapy resistance. However, the molecular characterization of CTCs remains a challenge because of the rarity and heterogeneity of CTCs and technological difficulties in the enrichment, isolation and molecular characterization of CTCs. In this pilot study, we evaluated circulating tumor associated cells in one blood draw by size exclusion technology and cytological analysis. Among 30 prospectively enrolled MBC patients, CTCs, circulating tumor cell clusters (CTC clusters), CTCs of epithelial–mesenchymal transition (EMT) and cancer associated macrophage-like cells (CAMLs) were detected and analyzed. For molecular characterization of CTCs, size-exclusion method for CTC enrichment was tested in combination with DEPArray™ technology, which allows the recovery of single CTCs or pools of CTCs as a pure CTC sample for mutation analysis. Genomic mutations of TP53 and ESR1 were analyzed by targeted sequencing on isolated 7 CTCs from a patient with MBC. The results of genomic analysis showed heterozygous TP53 R248W mutation from one single CTC and pools of three CTCs, and homozygous TP53 R248W mutation from one single CTC and pools of two CTCs. Wild-type ESR1 was detected in the same isolated CTCs. The results of this study reveal that size-exclusion method can be used to enrich and identify circulating tumor associated cells, and enriched CTCs were characterized for genetic alterations in MBC patients, respectively.

BACKGROUND: Single-cell genomics is an approach to investigate cell heterogeneity and to identify new molecular features correlated with clinical outcomes. This approach allows identification of the complexity of cell diversity in a sample without the loss of information that occurs when multicellular or bulk tissue samples are analyzed.CONTENT: The first single-cell RNA-sequencing study was published in 2009, and since then many more studies and single-cell sequencing methods have been published. These studies have had a major impact on several fields, including microbiology, neurobiology, cancer, and developmental biology. Recently, improvements in reliability and the development of commercial single-cell isolation platforms are opening the potential of this technology to the clinical laboratory.SUMMARY: In this review we provide an overview of the current state of single-cell genomics. We describe opportunities in clinical research and medical applications.

Background: Alzheimer's disease (AD) is one of the most common causes of dementia in old people. Neuronal deficits such as loss of memory, language and problem-solving are severely compromised in affected patients. The molecular features of AD are Aβ deposits in plaques or in oligomeric structures and neurofibrillary tau tangles in brain. However, the challenge is that Aβ is only one piece of the puzzle, and recent findings continue to support the hypothesis that their presence is not sufficient to predict decline along the AD outcome. In this regard, metabolomic-based techniques are acquiring a growing interest for either the early diagnosis of diseases or the therapy monitoring. Mass spectrometry is one the most common analytical platforms used for detection, quantification, and characterization of metabolic biomarkers. In the past years, both targeted and untargeted strategies have been applied to identify possible interesting compounds. Aim of review: The overall goal of this review is to guide the reader through the most recent studies in which LC–MS-based metabolomics has been proposed as a powerful tool for the identification of new diagnostic biomarkers in AD. To this aim, herein studies spanning the period 2009–2020 have been reported. Advantages and disadvantages of targeted vs untargeted metabolomic approaches have been outlined and critically discussed.

The COVID-19 pandemic has forced diagnostic laboratories to focus on the early diagnostics of SARS-CoV-2. The positivity of a molecular test cannot respond to the question regarding the viral capability to replicate, spread, and give different clinical effects. Despite the fact that some targets are covered by commercially-available assays, the identification of new biomarkers is desired in order to improve the quality of the information given by these assays. Therefore, since the subgenomic transcripts (sgN and sgE) are considered markers of viral activity, we evaluated these subgenomic transcripts in relation to the genomic amplification obtained using five different commercial CE-IVD tools. Methods: Five CE-IVD kits were compared in terms of their capability to detect both synthetic SARS-CoV-2 viral constructs (spiked in TMB or PBS medium) and targets (N, E, RdRp and Orf1ab genes) in twenty COVID-19–positive patients’ swabs. The sgN and sgE were assayed by real-time RT-qPCR and digital PCR. Results: None of the diagnostic kits missed the viral target genes when they were applied to targets spiked in TMB or PBS (at dilutions ranging from 100 pg to 0.1 pg). Nevertheless, once they were applied to RNA extracted from the patients’ swabs, the superimposability ranged from 50% to 100%, regardless of the extraction procedure. The sgN RNA transcript was detected only in samples with a higher viral load (Ct ≤ 22.5), while sgE was within all of the Ct ranges. Conclusions: The five kits show variable performances depending on the assay layout. It is worthy of note that the detection of the sgN transcript is associated with a higher viral load, thus representing a new marker of early and more severe infection.