Deciphering the Biology of Circulating Tumor Cells through Single-Cell RNA Sequencing: Implications for Precision Medicine in Cancer.

Circulating tumor cells (CTCs) hold unique biological characteristics that directly involve them in hematogenous dissemination. Studying CTCs systematically is technically challenging due to their extreme rarity and heterogeneity and the lack of specific markers to specify metastasis-initiating CTCs. With cutting-edge technology, single-cell RNA sequencing (scRNA-seq) provides insights into the biology of metastatic processes driven by CTCs. Transcriptomics analysis of single CTCs can decipher tumor heterogeneity and phenotypic plasticity for exploring promising novel therapeutic targets. The integrated approach provides a perspective on the mechanisms underlying tumor development and interrogates CTCs interactions with other blood cell types, particularly those of the immune system. This review aims to comprehensively describe the current study on CTC transcriptomic analysis through scRNA-seq technology. We emphasize the workflow for scRNA-seq analysis of CTCs, including enrichment, single cell isolation, and bioinformatic tools applied for this purpose. Furthermore, we elucidated the translational knowledge from the transcriptomic profile of individual CTCs and the biology of cancer metastasis for developing effective therapeutics through targeting key pathways in CTCs.

Characterization of Cell-Free DNA Size Distribution in Osteosarcoma Patients.

PURPOSE: Cell-free DNA (cfDNA) analysis is a powerful tool for noninvasively predicting patient outcomes. We analyzed the size distribution of cfDNA and assessed its prognostic and diagnostic values in an osteosarcoma cohort. EXPERIMENTAL DESIGN: The fragment size distribution and level of cfDNA were analyzed in 15 healthy donors and 50 patients with osteosarcoma using automated capillary electrophoresis. The prognostic performance of cfDNA size analysis was assessed using univariate and multivariable analyses. By performing whole-genome sequencing of matched cfDNA and osteosarcoma tissue samples, we investigated the correlation between the size and mutation profiles of cfDNA and the mutation concordance between cfDNA and paired tissue tumors. RESULTS: The size of cfDNA fragments in patients with osteosarcoma was significantly shorter than in healthy donors, with the integrative analysis of size distribution and level of cfDNA achieving a high specificity and sensitivity of 100%. The short cfDNA fragment (150-bp cut-off) was an independent prognostic predictor in this osteosarcoma cohort [HR, 9.03; 95% confidence interval (CI), 1.13-72.20; P = 0.038]. Shortened cfDNA fragments were found to be a major source of mutations. Enrichment of cfDNA fragments with less than or equal to 150 bp by in silico size selection remarkedly improved the detection of copy-number variation signals up to 2.3-fold when compared with total cfDNA, with a higher concordance rate with matched osteosarcoma tissue. CONCLUSIONS: This finding demonstrated the potential of cfDNA size profiling in the stratification of poor prognostic patients with osteosarcoma. The short fragments of cfDNA are a promising source for boosting the detection of significant mutations in osteosarcoma. See related commentary by Weiser et al., p. 2017.