The effect of adjuvant systemic therapy on prognostic impact of polymorphisms

<p><b>Copyright information:</b></p><p>Taken from "Association of codon 72 polymorphism and the outcome of adjuvant therapy in breast cancer patients"</p><p>http://breast-cancer-research.com/content/9/3/R34</p><p>Breast Cancer Research 2007;9(3):R34-R34.</p><p>Published online 30 May 2007</p><p>PMCID:PMC1929098.</p><p></p> codon 72 and adjuvant chemotherapy alone (= 137); codon 72 and adjuvant chemotherapy with or without hormonal therapy (= 281); codon 72 and adjuvant hormonal therapy alone (= 195); codon 72 and no adjuvant systemic therapy (= 77); SNP309 and adjuvant tamoxifen with or without luteinizing hormone-releasing hormone analog (= 185). DFS, disease-free survival

Development of a New Rapid Isolation Device for Circulating Tumor Cells (CTCs) Using 3D Palladium Filter and Its Application for Genetic Analysis

<div><p>Circulating tumor cells (CTCs) in the blood of patients with epithelial malignancies provide a promising and minimally invasive source for early detection of metastasis, monitoring of therapeutic effects and basic research addressing the mechanism of metastasis. In this study, we developed a new filtration-based, sensitive CTC isolation device. This device consists of a 3-dimensional (3D) palladium (Pd) filter with an 8 µm-sized pore in the lower layer and a 30 µm-sized pocket in the upper layer to trap CTCs on a filter micro-fabricated by precise lithography plus electroforming process. This is a simple pump-less device driven by gravity flow and can enrich CTCs from whole blood within 20 min. After on-device staining of CTCs for 30 min, the filter cassette was removed from the device, fixed in a cassette holder and set up on the upright fluorescence microscope. Enumeration and isolation of CTCs for subsequent genetic analysis from the beginning were completed within 1.5 hr and 2 hr, respectively. Cell spike experiments demonstrated that the recovery rate of tumor cells from blood by this Pd filter device was more than 85%. Single living tumor cells were efficiently isolated from these spiked tumor cells by a micromanipulator, and <i>KRAS</i> mutation, HER2 gene amplification and overexpression, for example, were successfully detected from such isolated single tumor cells. Sequential analysis of blood from mice bearing metastasis revealed that CTC increased with progression of metastasis. Furthermore, a significant increase in the number of CTCs from the blood of patients with metastatic breast cancer was observed compared with patients without metastasis and healthy volunteers. These results suggest that this new 3D Pd filter-based device would be a useful tool for the rapid, cost effective and sensitive detection, enumeration, isolation and genetic analysis of CTCs from peripheral blood in both preclinical and clinical settings.</p></div

Detection of CTCs from blood in the spontaneous metastasis model of nude mice after sc injection of GFP-tagged COLM-5 human colon cancer cells.

<p><b>A</b>–<b>I</b>. Sequential observation of lung and liver metastasis and detection of CTC in the blood of nude mice (arrows indicate lung metastasis). <b>A</b>–<b>D</b>. Micrometastasis in the lung 1–2 months post-injection (A, B. bright and dark field image of the lung, C. Fluorescence microscopic view of the lung, D. Liver). Bar = 3 mm. <b>E</b>–<b>I</b>. Macroscopic and microscopic metastasis in the lung 2–3 months post-injection (E, F. bright and dark field image of the Lung, G. Fluorescence microscopic view of the lung, H. Liver, I. Subcutaneous tumor). Bar = 3 mm. <b>J</b>–<b>K</b>. Representative single CTC in the blood from mice 1–2 months post-injection (n = 5). <b>L</b>–<b>M</b>. Representative CTC cluster in the blood from mice 2–3 months post-injection (n = 7). Bar = 30 µm. <b>N</b>. Changes in CTC number in the blood with time.</p

Detection and enumeration of CTC from patients with breast cancers.

<p><b>A</b>–<b>E</b>. Representative CTC cluster showing EpCAM+/CD45−/Hoechst33342+ pattern. <b>F</b>–<b>J</b>. Representative single CTC with EpCAM+/CD45−/Hoechst33342+ pattern. Arrows indicate CTC. <b>K</b>. Quantitative comparison of CTC number in blood from 19 patients with metastatic breast cancer (M1) and blood from 13 patients without metastasis (M0) and 12 healthy volunteers. Note that CTC was detected in 3 out of 13 M0 patients, but not detected at all in healthy volunteers. (A, F: Alexa488-EpCAM, B, G: PE-CD45, C, H: Hoechst33342, D, I: bright field, E, J: Merge image between EpCAM and bright field. *P<0.05 (vs M1), Bars = 30 µm.</p

Flowchart of enrichment, enumeration, isolation and molecular analysis of CTC by metal filtration-based device.

<p><b>A</b>. Overview of CTC enrichment device which consists of blood reservoir, filter unit and disposal tank. Filter unit (filter cassette) is composed of a palladium (Pd) metal filter placed between upper and lower cassette pieces. Diluted whole blood is applied to the reservoir and filtrated driven by gravity flow without a pump. <b>B</b>. After filtration, filter cassette is detached from the device and set up in combination with cassette holder on the upright fluorescence microscope for enumeration and isolation. <b>C</b>. Single CTC is isolated with micromanipulation using a glass capillary. Isolated CTC moved into PCR plate and DNA/RNA is extracted and amplified. Mutation and/or gene expression analysis is then performed. <b>D</b>. The filter is detached from cassette and is directly stained with immunocytochemistry (ICC) and FISH method.</p

Additional file 1: of Comparison of clinical outcomes between luminal invasive ductal carcinoma and luminal invasive lobular carcinoma

Dataset supporting the conclusions of this article. (XLSX 94 kb

Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease - Fig 4

<p><b>(Top panels) Circular plots of coexpression links between different locations on the genome, illustrating the spatial separation of highly-correlated regulatory regions.</b> The coloured outer circle shows an end-to-end concatenated view of the human chromosomes. The black inner circle shows –<i>log</i>₁₀ GWAS p-values for included SNPs. Links depict an association between two regulatory regions containing these SNPs and are coloured according to –<i>log</i>₁₀(<i>p</i>) (line colour indicates –<i>log</i>₁₀(<i>p</i>): red>3, blue> 2, green> 1.5). (Bottom panels) Quantile-quantile plots showing observed and expected coexpression scores. Expected coexpression scores are derived from circular permuted subsets of regulatory regions (post-mapping permutations; black circles) or SNPs chosen by circular permutations against the background of all SNPs genotyped in each study. Data are shown for high-density lipoprotein (HDL), low-density lipoprotein (LDL), and total cholesterol. See supplementary results for full results of all analyses.</p

Examples of detail of chromosomal regions surrounding regulatory regions significantly coexpressed in ulcerative colitis (TSS+/−150MbTSS+/-150Mb).

<p>(a) Region surrounding IL10 (b) Region surrounding C1orf106. Top panel: Coloured ectangles show genomic location of individual regulatory regions (promoters or enhancers). Height of regulatory regions on y-axis depicts the coexpression score assigned to this regulatory region; groups of regulatory regions considered as a single unit (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005934#sec002" target="_blank">Methods</a>) share the same colour. Black circles show GWAS $p$-values for individual SNPs. Red circles show causative probabilities estimated by Huang \emph{et al} for specific variants, where available. Bottom panel: genomic locations of known protein coding transcripts in sense (green) and antisense (purple).</p

Results of coexpression analysis for a range of human traits for which high-quality data are available: Crohn's disease, ulcerative colitis, high-density lipoprotein (HDL), low-density lipoprotein (LDL), total cholesterol, triglycerides, height, systolic blood pressure (SBP) and diastolic blood pressure (DBP).

<p>Results of coexpression analysis for a range of human traits for which high-quality data are available: Crohn's disease, ulcerative colitis, high-density lipoprotein (HDL), low-density lipoprotein (LDL), total cholesterol, triglycerides, height, systolic blood pressure (SBP) and diastolic blood pressure (DBP).</p

Examples of detail of chromosomal regions surrounding regulatory regions significantly coexpressed in ulcerative colitis (TSS+/-150Mb).

<p>(a) Region surrounding IL10 (b) Region surrounding C1orf106. Top panel: Coloured rectangles show genomic location of individual regulatory regions (promoters or enhancers). Height of regulatory regions on y-axis depicts the coexpression score assigned to this regulatory region; groups of regulatory regions considered as a single unit (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005934#sec002" target="_blank">Methods</a>) share the same colour. Black circles show GWAS p-values for individual SNPs. Red circles show causative probabilities estimated by Huang <i>et al</i> for specific variants, where available. Bottom panel: genomic locations of known protein coding transcripts in sense (green) and antisense (purple).</p