Ranking

http://ontario.compareschoolrankings.org/elementary/SchoolsByAreaMap.aspx
http://ontario.compareschoolrankings.org/secondary/SchoolsByAreaMap.aspx

http://www.imuc.com/pdf/Griffin-Industry-Report-09-14-2009.pdf

http://www.imuc.com/pdf/Griffin-Industry-Report-09-14-2009.pdf

Brain Cancer Stem Cells Display Preferential Sensitivity to Akt Inhibition
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2739007/


Breast CS CD44+/CD24-/Lin-
Prospective identification of tumorigenic breast cancer cells

BEZ235 vs CD44+

Combination Therapy Targeting Both Tumor-Initiating and Differentiated Cell Populations in Prostate Carcinoma

Results: Here, we show that inhibition of PI3K activity by the dual PI3K/mTOR inhibitor NVP-BEZ235 leads to a decrease in the population of CD133⁺/CD44⁺ prostate cancer progenitor cells in vivo. Moreover, the combination of the PI3K/mTOR modulator NVP-BEZ235, which eliminates prostate cancer progenitor populations, and the chemotherapeutic drug Taxotere, which targets the bulk tumor, is significantly more effective in eradicating tumors in a prostate cancer xenograft model than monotherapy.

Identification of Selective Inhibitors of Cancer Stem Cells by High-Throughput Screening

http://www.cell.com/retrieve/pii/S0092867409007818

http://www.workingincanada.gc.ca/report-eng.do?action=display_allnoc

http://www.workingincanada.gc.ca/report-eng.do?action=display_allnoc

gene profiling of cancer stem cell

http://www.google.com/search?q=gene+profiling+of+cancer+stem+cell&rls=com.microsoft:en-US&ie=UTF-8&oe=UTF-8&startIndex=&startPage=0


http://www.molecular-cancer.com/content/6/1/75

http://genomebiology.com/content/9/5/R83

cancer stem cells (CSCs) or tumor-initiating cells (TICs)

http://www.miltenyibiotec.com/en/NN_722_Tumor_stem_cells.aspx

Within a tumor, the majority of tumor cells have limited ability to proliferate and rather differentiate into cells that constitute the bulk of the tumor mass. Recent theories suggest that a small population of cells within some tumors possess the ability to self-renew and proliferate and are thus able to maintain the tumor. These cells, which are called cancer stem cells (CSCs) or tumor-initiating cells (TICs), have been observed to share certain characteristics with normal stem cells, including a stem cell–like phenotype and function.

Certain surface markers that are associated with stem cells are also found on cancer stem cells. Human and mouse stem cell markers such as CD34, CD133,CD117, Sca-1, and other markers, such as CD44, CD24, CD20, CD105, andCD326 (EpCAM) have been found on cancer stem cells. This particular type of cell seems to be able to initiate and drive tumor growth in different hematological and solid tumors. It is critical to be able to identify and isolate these cells from tumor tissues in order to provide a clearer picture of the mechanisms governing the establishment of CSCs, their maintenance, and the molecular alteration in comparison to normal cells. An enrichment of CSCs has been observed in cell populations selected for CD133 expression from brain tumor^1–4, prostate cancer⁵, renal tumors⁶, and also recently from colon cancer^7,8 and hepatocellular carcinoma⁹.

To view the respective citations and a list of associated products, please download the attached PDF file.

PCA

#Here the object data is the gene expression from RMA with dimension pxn = 54675 x 248, here n=248 (two batches: 192+56)

genes<-data[1:54613,]

genes<-t(genes)

pcs<-prcomp(genes)

summary(pcs)

library(scatterplot3d)

PC1<-pcs$x[,1]

PC2<-pcs$x[,2]

PC3<-pcs$x[,3]

group.colors <- rep("#000000", length(PC1))

group.colors[seq(1,192,1)] = "#FF77FF"   #SG Batch A

group.colors[seq(193,248,1)] = "blue"      #SG Batch B

scatterplot3d(PC3,PC1,PC2, main="PCA scatterplot before ComBat normalization", color=group.colors, pch=16)

legend.txt <- c("SG Batch A", "SG Batch B")

legend.col <- c("#00FF00","#0000FF")

legend(-5.75, 5.2, legend.txt , bty="n", col=legend.col,cex=1.2, pch=15)

Cancer Guide

http://www.cancerguide.org/pathology.html

Boxplot

GP130 <- c(0.016, 0.023, 0.028, 0.030, 0.037, 0.040, 0.045, 0.051, 0.055, 0.070, 0.071, 0.075, 0.075, 0.076, 0.088, 0.092, 0.094, 0.095, 0.096, 0.097, 0.105, 0.114, 0.123, 0.135, 0.146, 0.163, 0.165, 0.176, 0.187, 0.199, 0.200, 0.214, 0.215, 0.249, 0.256, 0.263, 0.273, 0.302, 0.317, 0.330, 0.361, 0.364, 0.380, 0.386, 0.390, 0.392, 0.393, 0.449, 0.480, 0.494, 0.500, 0.514, 0.536, 0.541, 0.545, 0.562, 0.587, 0.647, 0.652, 0.662, 0.685, 0.696, 0.709, 0.718, 0.719, 0.741, 0.747, 0.799, 0.805, 0.805, 0.821, 0.870, 0.901, 0.988, 0.994, 0.008, 0.017, 0.017, 0.028, 0.030, 0.039, 0.045, 0.067, 0.085, 0.204, 0.223, 0.264, 0.276, 0.289, 0.290, 0.303, 0.314, 0.320, 0.346, 0.363, 0.365, 0.372, 0.380, 0.386, 0.389, 0.391, 0.408, 0.441, 0.446, 0.449, 0.460, 0.471, 0.472, 0.485, 0.492, 0.497, 0.498, 0.500, 0.501, 0.502, 0.508, 0.513, 0.527, 0.528, 0.529, 0.543, 0.585, 0.604, 0.612, 0.621, 0.628, 0.651, 0.652, 0.672, 0.688, 0.688, 0.702, 0.704, 0.704, 0.709, 0.716, 0.723, 0.727, 0.730, 0.736, 0.743, 0.749, 0.751, 0.758, 0.762, 0.764, 0.766, 0.772, 0.779, 0.780, 0.783, 0.784, 0.787, 0.800, 0.803, 0.814, 0.819, 0.824, 0.826, 0.831, 0.836, 0.837, 0.840, 0.843, 0.860, 0.903, 0.931, 0.948, 0.960, 0.968, 0.974, 0.983, 0.991, 0.999)



Lauren <- c("Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Diffuse", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal", "Intestinal")



p <- t.test(GP130~Lauren)$p.value



#p <- lapply(p, signif, 3)

p <- signif(p, 3)



 boxplot( as.numeric(GP130) ~ Lauren, col=c("#FFC000", "#0070C0"),  medlwd = 2, lwd = 2, outlwd=1, cex.axis=1.2, ylab="GP130 activation score")



legend(2.05,0.2, paste("p = ", p, sep=""), box.col ="white")



setwd('E:/Projects/GP130')



pdf(file='SG192.boxplot.pdf')



 boxplot( as.numeric(GP130) ~ Lauren, col=c("#FFC000", "#0070C0"),  medlwd = 2, lwd = 2, outlwd=1, cex.axis=1.2, ylab="GP130 activation score")



legend(2.05,0.2, paste("p = ", p, sep=""), box.col ="white")



dev.off()