Autoimmunity plays a key role in the immunopathogenesis of psoriasis; however, little is known about the recruitment of pathogenic cells to skin lesions. We report here that the CC chemokine, macrophage inflammatory protein-3α, recently renamed CCL20, and its receptor CCR6 are markedly up-regulated in psoriasis. CCL20-expressing keratinocytes colocalize with skin-infiltrating T cells in lesional psoriatic skin. PBMCs derived from psoriatic patients show significantly increased CCR6 mRNA levels. Moreover, skin-homing CLA+ memory T cells express high levels of surface CCR6. Furthermore, the expression of CCR6 mRNA is 100- to 1000-fold higher on sorted CLA+ memory T cells than other chemokine receptors, including CXCR1, CXCR2, CXCR3, CCR2, CCR3, and CCR5. In vitro, CCL20 attracted skin-homing CLA+ T cells of both normal and psoriatic donors; however, psoriatic lymphocytes responded to lower concentrations of chemokine and showed higher chemotactic responses. Using ELISA as well as real-time quantitative PCR, we show that cultured primary keratinocytes, dermal fibroblasts, and dermal microvascular endothelial and dendritic cells are major sources of CCL20, and that the expression of this chemokine can be induced by proinflammatory mediators such as TNF-α/IL-1β, CD40 ligand, IFN-γ, or IL-17. Taken together, these findings strongly suggest that CCL20/CCR6 may play a role in the recruitment of T cells to lesional psoriatic skin.

BackgroundTo improve cancer therapy, it is critical to target metastasizing cells. Circulating tumor cells (CTCs) are rare cells found in the blood of patients with solid tumors and may play a key role in cancer dissemination. Uncovering CTC phenotypes offers a potential avenue to inform treatment. However, CTC transcriptional profiling is limited by leukocyte contamination; an approach to surmount this problem is single cell analysis. Here we demonstrate feasibility of performing high dimensional single CTC profiling, providing early insight into CTC heterogeneity and allowing comparisons to breast cancer cell lines widely used for drug discovery.Methodology/Principal FindingsWe purified CTCs using the MagSweeper, an immunomagnetic enrichment device that isolates live tumor cells from unfractionated blood. CTCs that met stringent criteria for further analysis were obtained from 70% (14/20) of primary and 70% (21/30) of metastatic breast cancer patients; none were captured from patients with non-epithelial cancer (n = 20) or healthy subjects (n = 25). Microfluidic-based single cell transcriptional profiling of 87 cancer-associated and reference genes showed heterogeneity among individual CTCs, separating them into two major subgroups, based on 31 highly expressed genes. In contrast, single cells from seven breast cancer cell lines were tightly clustered together by sample ID and ER status. CTC profiles were distinct from those of cancer cell lines, questioning the suitability of such lines for drug discovery efforts for late stage cancer therapy.Conclusions/SignificanceFor the first time, we directly measured high dimensional gene expression in individual CTCs without the common practice of pooling such cells. Elevated transcript levels of genes associated with metastasis NPTN, S100A4, S100A9, and with epithelial mesenchymal transition: VIM, TGFß1, ZEB2, FOXC1, CXCR4, were striking compared to cell lines. Our findings demonstrate that profiling CTCs on a cell-by-cell basis is possible and may facilitate the application of ‘liquid biopsies’ to better model drug discovery.

Individual cell heterogeneity within a population can be critical to its peculiar function and fate. Subpopulations studies with mixed mutants and wild types may not be as informative regarding which cell responds to which drugs or clinical treatments. Cell to cell differences in RNA transcripts and protein expression can be key to answering questions in cancer, neurobiology, stem cell biology, immunology, and developmental biology. Conventional cell-based assays mainly analyze the average responses from a population of cells, without regarding individual cell phenotypes. To better understand the variations from cell to cell, scientists need to use single cell analyses to provide more detailed information for therapeutic decision making in precision medicine. In this review, we focus on the recent developments in single cell isolation and analysis, which include technologies, analyses and main applications. Here, we summarize the historical background, limitations, applications, and potential of single cell isolation technologies.

Introduction Circulating tumor cells (CTCs) are detectable in most cancer patients and they can meet an existing medical need to monitor cancer patients during a course of treatment and to help determine recurrent disease. CTCs are rarely found in the blood of cancer patients and enrichment is necessary for sensitive CTC detection. Most CTC enrichment technologies are anti-EpCAM antibody based even though CTC identification criteria are cytokeratin positive (CK + ), CD45 negative (CD45 - ) and 4'6-diamidino-2-phenylindole (nuclear stain) positive (DAPI + ). However, some tumor cells express low or no EpCAM. Here we present a highly sensitive and reproducible enrichment method that is based on binding to anti-CK alone or a combination of anti-CK and anti-EpCAM antibodies. Methods Blood samples from 49 patients with metastatic breast cancer were processed using the CellSearch™ system (Veridex, LLC, Raritan, NJ, USA), in parallel with our CTC assay method. We used anti-CK alone or in combination with anti-EpCAM antibodies for CTC enrichment. Brightfield and fluorescence labeled anti-CK, anti-CD45 and DAPI (nuclear stain) images were used for CTC identification. The Ariol ® system (Genetix USA Inc, San Jose, CA, USA) was used for automated cell image capture and analysis of CTCs on glass slides. Results Our method has the capability to enrich three types of CTCs including CK + &EpCAM + , CK + &EpCAM -/low , and CK -/low &EpCAM + cells. In the blind method comparison, our anti-CK antibody enrichment method showed a significantly higher CTC positive rate (49% vs. 29%) and a larger dynamic CTC detected range (1 to 571 vs. 1 to 270) than that of the CellSearch™ system in the total of 49 breast cancer patients. Our method detected 15 to 111% more CTCs than the CellSearch™ method in patients with higher CTC counts (>20 CTCs per 7.5 ml of blood). The three fluorescent and brightfield images from the Ariol ® system reduced the number of false-positive CTC events according to the established CTC criteria. Conclusion Our data indicate that the tumor-specific intracellular CK marker could be used for efficient CTC enrichment. Enrichment with anti-CK alone or combined with anti-EpCAM antibodies significantly enhances assay sensitivity. The three fluorescent and brightfield superior images with the Ariol ® system reduced false-positive CTC events.

Gene expression analysis has become an invaluable tool for understanding gene function and regulation. However, global expression analysis requires large RNA quantities or RNA preamplification. We describe an isothermal messenger RNA (mRNA) amplification method, Ribo-SPIA, which generates micrograms of labeled cDNA from 5 ng of total RNA in 1 day for analysis on arrays or by PCR quantification. Highly reproducible GeneChip array performance (R2 > 0.95) was achieved with independent reactions starting with 5-100 ng Universal Human Reference total RNA. Targets prepared by the Ribo-SPIA procedure (20 ng total RNA input) or the Affymetrix Standard Protocol (10 microg total RNA) perform similarly, as indicated by gene call concordance (86%) and good correlation of differential gene expression determination (R2 = 0.82). Accuracy of transcript representation in cDNA generated by the Ribo-SPIA procedure was also demonstrated by PCR quantification of 33 transcripts, comparing differential expression in amplified and nonamplified cDNA (R2 = 0.97 over a range of nearly 10(6) infold change). Thus Ribo-SPIA amplification of mRNA is rapid, robust, highly accurate and reproducible, and sensitive enough to allow quantification of very low abundance transcripts.