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In the last decades, several gene expression-based predictors of clinical behavior were developed for breast cancer. A common feature of these is the use of multiple genes to predict hormone receptor status and the probability of tumor recurrence, survival or response to chemotherapy. We developed an online analysis tool to compute ER and HER2 status, Oncotype DX 21-gene recurrence score and an independent recurrence risk classification using gene expression data obtained by interrogation of Affymetrix microarray profiles. We implemented rigorous quality control algorithms to promptly exclude any biases related to sample processing, hybridization and scanning. After uploading the raw microarray data, the system performs the complete evaluation automatically and provides a report summarizing the results. The system is accessible online at . We validated the system using data from 2,472 publicly available microarrays. The validation of the prediction of the 21-gene recurrence score was significant in lymph node negative patients (Cox-Mantel, P = 5.6E-16, HR = 0.4, CI = 0.32-0.5). A correct classification was obtained for 88.5% of ER- and 90.5% of ER + tumors ( n = 1,894). The prediction of recurrence risk in all patients by using the mean of the independent six strongest genes ( P < 1E-16, HR = 2.9, CI = 2.5-3.3), of the four strongest genes in lymph node negative ER positive patients ( P < 1E-16, HR = 2.8, CI = 2.2-3.5) and of the three genes in lymph node positive patients ( P = 3.2E-9, HR = 2.5, CI = 1.8-3.4) was highly significant. In summary, we integrated available knowledge in one platform to validate currently used predictors and to provide a global tool for the online determination of different prognostic parameters simultaneously using genome-wide microarrays. [ABSTRACT FROM AUTHOR]

The transcriptome of breast cancers have been extensively screened with microarrays and large sets of genes associated with clinical features have been established. The aim of this study was to validate original gene sets on a large cohort of raw breast cancer microarray data with known clinical follow-up. We recovered 20 publications and matched them to Affymetrix HGU133A annotations. Raw Affymetrix HGU133A microarray data were extracted from GEO and MAS5 normalized. For classifying patients using the selected gene sets, we applied prediction analysis of microarrays and constructed Kaplan–Meier plots. A new classification including all patients was generated using supervised principal components analysis. Seven studies including 1,470 patients were downloaded from GEO. Notably, we uncovered 641 microarrays representing 251 individual tumor specimens among them, which were repeatedly described under independent GEO identifiers. We excluded all redundant data and used the remaining 1,079 samples. Eight of the 20 gene sets were able to predict response at a significance of P < 0.05. The discrimination of good and poor prognosis groups exclusively relying on gene expression data resulted in high significance ( P = 1.8E−12). A model including genes fitted by both gene expression and clinical covariates (lymph node status and grade) contains 44 genes and can predict response at P = 9.5E−7. The outcome provides a ranking of the gene lists regarding applicability on an independent dataset. We established a consensus predictor combining the available clinical and gene expression data. The database comprising expression profiles of 1,079 breast cancers can be used to classify individual patients. [ABSTRACT FROM AUTHOR]

To understand the extreme complexity of biological events requires a systemic approach. This holds particularly for the disordered biological interactions that are characteristic of disease, the subject of pathology. Which options are available to untie the Gordian knot? In this contribution, the potential role of systems biology and, as a further development, systems pathology will be discussed. [ABSTRACT FROM AUTHOR]

Up to date clinical tests for predicting cancer chemotherapy response are not available and individual markers have shown little predictive value. We hypothesized that gene expression patterns attributable to chemotherapy-resistant cells can predict response and cancer prognosis. We contrasted the expression profiles of 13 different human tumor cell lines of gastric (EPG85–257), pancreatic (EPP85–181), colon (HT29) and breast (MCF7 and MDA-MB-231) origin and their counterparts resistant to the topoisomerase inhibitors daunorubicin, doxorubicin or mitoxantrone. We interrogated cDNA arrays with 43 000 cDNA clones (∼30 000 unique genes) to study the expression pattern of these cell lines. We divided gene expression profiles into two sets: we compared the expression patterns of the daunorubicin/doxorubicin-resistant cell lines and the mitoxantrone-resistant cell lines independently to the parental cell lines. For identifying predictive genes, the Prediction Analysis for Mircorarrays algorithm was used. The analysis revealed 79 genes best correlated with doxorubicin resistance and 70 genes with mitoxantrone resistance. In an independent classification experiment, we applied our model of resistance for predicting the sensitivity of 44 previously characterized breast cancer samples. The patient group characterized by the gene expression profile similar to those of doxorubicin-sensitive cell lines exhibited longer survival (49.7±26.1 months, n=21, P=0.034) than the resistant group (32.9±18.7 months, n=23). The application of gene expression signatures derived from doxorubicin-resistant and -sensitive cell lines allowed to predict effectively clinical survival after doxorubicin monotherapy. Our approach demonstrates the significance of in vitro experiments in the development of new strategies for cancer response prediction.Oncogene (2005) 24, 7542–7551. doi:10.1038/sj.onc.1208908; published online 25 July 2005 [ABSTRACT FROM AUTHOR]

To understand the relationship between oncogenic signaling and the reprogramming of gene expression, we performed transcriptional profiling in rat ovarian surface epithelial cells (ROSE), in which neoplastic transformation is driven by a mutated KRAS oncogene. We identified >200 genes whose expression was elevated or reduced following permanent KRAS expression. Deregulated KRAS-responsive genes encode transcriptional regulators, signaling effectors, proteases, extracellular matrix and adhesion proteins, transformation-suppressing proteins and negative growth regulators. Many of them have not been previously identified in cells expressing oncogenic RAS genes or in other well-studied models of oncogenic signaling. The number of critical genes related to the execution of anchorage-independent proliferation and epithelial-mesenchymal transition was narrowed down to 79 by selectively inhibiting the mitogen-activated protein kinase (MAPK/ERK) and phosphatidylinositol 3-kinase (PI3K) pathways. Blocking MAPK/ERK-signaling caused reversion to the normal epithelial phenotype in conjunction with the reversal of deregulated target transcription to pretransformation levels. In addition, silencing of the overexpressed transcriptional regulator Fra-1 by RNA interference resulted in growth reduction, suggesting that this factor partially contributes to, but is not sufficient for the proliferative capacity of KRAS-transformed epithelial cells.Oncogene (2004) 23, 4536-4555. doi:10.1038/sj.onc.1207585 Published online 5 April 2004 [ABSTRACT FROM AUTHOR]

An important aspect of multi-step tumorigenesis is the mutational activation of genes of the RAS family, particularly in sporadic cancers of the pancreas, colon, lung and myeloid system. RAS genes encode small GTP-binding proteins that affect gene expression in a global way by acting as major switches in signal transduction processes, coupling extracellular signals with transcription factors. Oncogenic forms of RAS are locked in their active state and transduce signals essential for transformation, angiogenesis, invasion and metastasis via downstream pathways involving the RAF/MEK/ERK cascade of cytoplasmic kinases, the small GTPbinding proteins RAC and RHO, phosphatidylinositol 3-kinase and others. We have used subtractive suppression hybridization (SSH), a PCR-based cDNA subtraction technique, to contrast differential gene expression profiles in immortalized, non-tumorigenic rat embryo fibroblasts and in HRAS-transformed cells. Sequence and expression analysis of more than 1,200 subtracted cDNA fragments revealed transcriptional stimulation or repression of 104 ESTs, 45 novel sequences and 244 known genes in HRAS-transformed cells compared with normal cells. Furthermore, we identified common and distinct targets in cells transformed by mutant HRAS, KRAS and NRAS, as well as 61 putative target genes controlled by the RAF/MEK/ERK pathway in reverted cells treated with the MEK-specific inhibitor PD 98059. [ABSTRACT FROM AUTHOR]

The signal-transducing Ras proteins are important driving forces of diverse cellular processes such as proliferation, neoplastic transformation, differentiation and growth inhibition. As a step toward understanding the complex mechanisms underlying cellular responses, gene expression patterns were examined in two phenotypically normal fibroblast lines which differ in their sensitivity toward oncogene-mediated transformation. Suppression subtractive hybridization (SSH) was used to establish a subtracted cDNA library specific for the REF52 cell line which, like normal diploid fibroblasts, is refractory toward neoplastic transformation induced by mutated HRAS oncogenes. In contrast, rat 208F control cells can be efficiently transformed by HRAS. The nucleotide sequence of 549 subtracted cDNA clones (`REF52 minus 208F') was determined. We identified 93 preferentially expressed gene fragments in resistant REF52 cells as compared to 208F cells. Seventeen of the 52 known genes (32.6%) are capable of inhibiting cell proliferation or of adversely affecting oncogenic signal transduction pathways. These results suggest that the anti-oncogenic properties of resistant REF52 cells are determined by multiple negative growth regulators. The preneoplastic state expressed in 208F cells is characterized by impairment of unexpectedly redundant control mechanisms. Our results also demonstrate that SSH is a powerful method for identifying specific transcriptional patterns in closely related cell types. [ABSTRACT FROM AUTHOR]

The H-rev107 tumour suppressor was isolated as a gene specifically expressed in rat fibroblasts resistant toward malignant transformation by the activated HRAS gene (; ). Here we describe the human homologue of the rat H-rev107 gene. The predicted rat and human proteins are highly conserved exhibiting an overall amino acid identity of 83%. The H-REV107-1 gene is ubiquitously expressed with the exception of haematopoetic cells and tissues. In contrast, H-REV107-1 mRNA was found only in eight of 27 cell lines derived from mammary carcinoma, lung carcinoma, gastric carcinoma, kidney carcinoma, melanoma, neuroblastoma and other tumours. The H-REV107-1 protein was not detectable in any of these tumour cells. Loss of H-REV107-1 expression was not restricted to cultured human tumour cell lines, but also found in primary squamous cell carcinomas. Gross structural aberrations of the H-REV107-1 gene were absent in tumorigenic cell lines. Thus, the block to H-REV107-1 expression is achieved both at the level of transcription and translation. By fluorescence in situ hybridisation the human H-REV107-1 gene was localised to chromosome 11q11-12. [ABSTRACT FROM AUTHOR]

Resting cells of Clostridium sticklandii took up thymine or uracil, when grown in a medium containing 40 mM serine and 20 mM thymine or uracil. The uptake was much lower, when the cells had been grown in a complex medium. Cell-free extracts from cells grown in the complex medium reduced the two bases to the dihydro compounds and decomposed dihydrothymine to β-ureidoisobutyrate, as indicated by thin-layer chromatography. Uptake and degradation were stimulated by both NADH and NADPH. Further breakdown did not occur, as CO was not evolved from C-2-labelled thymine or uracil. The rates of pyrimidine uptake and breakdown of C. sticklandii were lower than those reported for C. sporogenes (Hilton et al., 1975). [ABSTRACT FROM AUTHOR]

The Stickland reaction was studied in suspensions of starved cells of Clostridium sticklandii with the aid of NADH fluorescence, and enzymic determinations of NADH. [ABSTRACT FROM AUTHOR]

The chromosomal assignment of the gene encoding the invariant (Ii) chain associated with the mouse immune response antigens (la) was determined by Southern blot analysis of DNA from a panel of mouse x Chinese hamster somatic cell hybrids cleaved with Hind III or Eco RI. Using a mouse Ii cDNA as a hybridization probe, we localized the gene coding for the invariant chain to mouse chromosome 18. [ABSTRACT FROM AUTHOR]