A combinatorial extracellular matrix platform identifies cell-extracellular matrix interactions that correlate with metastasis

Extracellular matrix interactions have essential roles in normal physiology and many pathological processes. Although the importance of extracellular matrix interactions in metastasis is well documented, systematic approaches to identify their roles in distinct stages of tumorigenesis have not been described. Here we report a novel-screening platform capable of measuring phenotypic responses to combinations of extracellular matrix molecules. Using a genetic mouse model of lung adenocarcinoma, we measure the extracellular matrix-dependent adhesion of tumour-derived cells. Hierarchical clustering of the adhesion profiles differentiates metastatic cell lines from primary tumour lines. Furthermore, we uncovered that metastatic cells selectively associate with fibronectin when in combination with galectin-3, galectin-8 or laminin. We show that these molecules correlate with human disease and that their interactions are mediated in part by α3β1 integrin. Thus, our platform allowed us to interrogate interactions between metastatic cells and their microenvironments, and identified extracellular matrix and integrin interactions that could serve as therapeutic targets.National Institutes of Health (U.S.) (Grant K99-CA151968)National Institutes of Health (U.S.). Ruth L. Kirschstein National Research Service AwardStand Up To Cancer (SU2C/AACR)David H. Koch Institute for Integrative Cancer Research at MIT (CTC Project)Harvard Stem Cell Institute (SG-0046-08-00)National Cancer Center (Postdoctoral Fellowship)National Cancer Institute (U.S.) (U54CA126515)National Cancer Institute (U.S.) (U54CA112967)Howard Hughes Medical InstituteMassachusetts Institute of Technology. Ludwig Center for Molecular Oncolog

In Silico Ascription of Gene Expression Differences to Tumor and Stromal Cells in a Model to Study Impact on Breast Cancer Outcome

Breast tumors consist of several different tissue components. Despite the heterogeneity, most gene expression analyses have traditionally been performed without prior microdissection of the tissue sample. Thus, the gene expression profiles obtained reflect the mRNA contribution from the various tissue components. We utilized histopathological estimations of area fractions of tumor and stromal tissue components in 198 fresh-frozen breast tumor tissue samples for a cell type-associated gene expression analysis associated with distant metastasis. Sets of differentially expressed gene-probes were identified in tumors from patients who developed distant metastasis compared with those who did not, by weighing the contribution from each tumor with the relative content of stromal and tumor epithelial cells in their individual tumor specimen. The analyses were performed under various assumptions of mRNA transcription level from tumor epithelial cells compared with stromal cells. A set of 30 differentially expressed gene-probes was ascribed solely to carcinoma cells. Furthermore, two sets of 38 and five differentially expressed gene-probes were mostly associated to tumor epithelial and stromal cells, respectively. Finally, a set of 26 differentially expressed gene-probes was identified independently of cell type focus. The differentially expressed genes were validated in independent gene expression data from a set of laser capture microdissected invasive ductal carcinomas. We present a method for identifying and ascribing differentially expressed genes to tumor epithelial and/or stromal cells, by utilizing pathologic information and weighted t-statistics. Although a transcriptional contribution from the stromal cell fraction is detectable in microarray experiments performed on bulk tumor, the gene expression differences between the distant metastasis and no distant metastasis group were mostly ascribed to the tumor epithelial cells of the primary breast tumors. However, the gene PIP5K2A was found significantly elevated in stroma cells in distant metastasis group, compared to stroma in no distant metastasis group. These findings were confirmed in gene expression data from the representative compartments from microdissected breast tissue. The method described was also found to be robust to different histopathological procedures

Quantitative Proteomic Analysis of Human Embryonic Stem Cell Differentiation by 8-Plex iTRAQ Labelling

Analysis of gene expression to define molecular mechanisms and pathways involved in human embryonic stem cells (hESCs) proliferation and differentiations has allowed for further deciphering of the self-renewal and pluripotency characteristics of hESC. Proteins associated with hESCs were discovered through isobaric tags for relative and absolute quantification (iTRAQ). Undifferentiated hESCs and hESCs in different stages of spontaneous differentiation by embryoid body (EB) formation were analyzed. Using the iTRAQ approach, we identified 156 differentially expressed proteins involved in cell proliferation, apoptosis, transcription, translation, mRNA processing, and protein synthesis. Proteins involved in nucleic acid binding, protein synthesis, and integrin signaling were downregulated during differentiation, whereas cytoskeleton proteins were upregulated. The present findings added insight to our understanding of the mechanisms involved in hESC proliferation and differentiation

Real-time PCR complements immunohistochemistry in the determination of HER-2/neu status in breast cancer

BACKGROUND: The clinical benefit of determining the status of HER-2/neu amplification in breast cancer patients is well accepted. Although immunohistochemistry (IHC) is the most frequently used method to assess the over-expression of HER-2 protein, fluorescent in-situ hybridization (FISH) is recognized as the "gold standard" for the determining of HER-2/neu status. The greatest discordance between the two methods occurs among breast tumors that receive an indeterminate IHC score of 2+. More recently, a real-time polymerase chain reaction (PCR) assay using the LightCycler(® )has been developed for quantifying HER-2/neu gene amplification. In this study, we evaluated the sensitivity and specificity of a commercially available LightCycler assay as it compares to FISH. To determine whether this assay provides an accurate alternative for the determination of HER-2/neu status, we focused primarily on tumors that were deemed indeterminate or borderline status by IHC. METHODS: Thirty-nine breast tumors receiving an IHC score of 2+ were evaluated by both FISH and LightCycler(® )technologies in order to determine whether quantitative real-time PCR provides an accurate alternative for the determination of HER-2/neu status. RESULTS: We found a high concordance (92%) between FISH and real-time PCR results. We also observed that 10% of these tumors were positive for gene amplification by both FISH and real-time PCR. CONCLUSION: The data show that the results obtained for the gene amplification of HER-2/neu by real-time PCR on the LightCycler(® )instrument is comparable to results obtained by FISH. These results therefore suggest that real-time PCR analysis, using the LightCycler(®), is a viable alternative to FISH for reassessing breast tumors which receive an IHC score of 2+, and that a combined IHC and real-time PCR approach for the determination of HER-2 status in breast cancer patients may be an effective and efficient strategy

Znf202 Affects High Density Lipoprotein Cholesterol Levels and Promotes Hepatosteatosis in Hyperlipidemic Mice

Background: The zinc finger protein Znf202 is a transcriptional suppressor of lipid related genes and has been linked to hypoalphalipoproteinemia. A functional role of Znf202 in lipid metabolism in vivo still remains to be established. Methodology and Principal Findings: We generated mouse Znf202 expression vectors, the functionality of which was established in several in vitro systems. Next, effects of adenoviral znf202 overexpression in vivo were determined in normo- as well as hyperlipidemic mouse models. Znf202 overexpression in mouse hepatoma cells mhAT3F2 resulted in downregulation of members of the Apoe/c1/c2 and Apoa1/c3/a4 gene cluster. The repressive activity of Znf202 was firmly confirmed in an apoE reporter assay and Znf202 responsive elements within the ApoE promoter were identified. Adenoviral Znf202 transfer to Ldlr-/- mice resulted in downregulation of apoe, apoc1, apoa1, and apoc3 within 24 h after gene transfer. Interestingly, key genes in bile flux (abcg5/8 and bsep) and in bile acid synthesis (cyp7a1) were also downregulated. At 5 days post-infection, the expression of the aforementioned genes was normalized, but mice had developed severe hepatosteatosis accompanied by hypercholesterolemia and hypoalphalipoproteinemia. A much milder phenotype was observed in wildtype mice after 5 days of hepatic Znf202 overexpression. Interestingly and similar to Ldl-/- mice, HDL-cholesterol levels in wildtype mice were lowered after hepatic Znf202 overexpression. Conclusion/Significance: Znf202 overexpression in vivo reveals an important role of this transcriptional regulator in liver lipid homeostasis, while firmly establishing the proposed key role in the control of HDL levels

A new method for class prediction based on signed-rank algorithms applied to Affymetrix® microarray experiments

<p>Abstract</p> <p>Background</p> <p>The huge amount of data generated by DNA chips is a powerful basis to classify various pathologies. However, constant evolution of microarray technology makes it difficult to mix data from different chip types for class prediction of limited sample populations. Affymetrix^®technology provides both a quantitative fluorescence signal and a decision (<it>detection call</it>: absent or present) based on signed-rank algorithms applied to several hybridization repeats of each gene, with a per-chip normalization. We developed a new prediction method for class belonging based on the detection call only from recent Affymetrix chip type. Biological data were obtained by hybridization on U133A, U133B and U133Plus 2.0 microarrays of purified normal B cells and cells from three independent groups of multiple myeloma (MM) patients.</p> <p>Results</p> <p>After a call-based data reduction step to filter out non class-discriminative probe sets, the gene list obtained was reduced to a predictor with correction for multiple testing by iterative deletion of probe sets that sequentially improve inter-class comparisons and their significance. The error rate of the method was determined using leave-one-out and 5-fold cross-validation. It was successfully applied to (i) determine a sex predictor with the normal donor group classifying gender with no error in all patient groups except for male MM samples with a Y chromosome deletion, (ii) predict the immunoglobulin light and heavy chains expressed by the malignant myeloma clones of the validation group and (iii) predict sex, light and heavy chain nature for every new patient. Finally, this method was shown powerful when compared to the popular classification method Prediction Analysis of Microarray (PAM).</p> <p>Conclusion</p> <p>This normalization-free method is routinely used for quality control and correction of collection errors in patient reports to clinicians. It can be easily extended to multiple class prediction suitable with clinical groups, and looks particularly promising through international cooperative projects like the "Microarray Quality Control project of US FDA" MAQC as a predictive classifier for diagnostic, prognostic and response to treatment. Finally, it can be used as a powerful tool to mine published data generated on Affymetrix systems and more generally classify samples with binary feature values.</p

20-Year Risks of Breast-Cancer Recurrence after Stopping Endocrine Therapy at 5 Years

The administration of endocrine therapy for 5 years substantially reduces recurrence rates during and after treatment in women with early-stage, estrogen-receptor (ER)-positive breast cancer. Extending such therapy beyond 5 years offers further protection but has additional side effects. Obtaining data on the absolute risk of subsequent distant recurrence if therapy stops at 5 years could help determine whether to extend treatment

Marker-Assisted Selection for Biotic Stress Resistance in Peanut

Peanut is the second-most important legume grown worldwide. Cultivated peanut is a disomic tetraploid, 2n—4x—40, with limited genetic diversity due to a genetic bottleneck in formation of the polyploid from ancestors A. duranensis and A. ipaensis. Consequently, resistance_to biotic stresses is limited in the cultigen; however, wild species possess strong resistances. Transfer o f these resistances is hindered by differences o f ploidy, but production o f synthetic amphidiploids, coupled with use o f molecular markers, enables efficient gene transfer. Marker maps have been made from interspecific crosses, and SSR-based maps from cultivated parents have been developed recently. At least 410 resistance gene analogues have been identified. The first markers for biotic stress tolerance were for root-knot nematode resistance and introgressed from one A. cardenasii chromosome. These and improved markers have been used for marker-assisted backcrossing, contributing to release of three cultivars. Additional QTLs have been identified since. Early and late leafspots cause significant yield losses worldwide, and resistance depends on multiple genes. Using interspecific populations, five resistance QTLs for early leafspot were identified using greenhouse inoculations, and five QTLs for late leafspot were identified using detached leaf assays. Using cultivated species populations, 28 QTLs were identified for LLS resistance; all but one were minor QTLs; the major QTL was donated by an interspecific introgression line parent. Rust often occurs alongside leafspots, and rust resistance was characterized as one major QTL, plus several smaller QTLs. Marker-assisted backcrossing o f this major QTL has been performed into different populations. QTLs for resistance to other biotic stresses have been identified, namely to groundnut rosette virus, Sclerotinia blight, afiatoxin contamination, aphids, and tomato spotted wilt virus. Marker-assisted breeding is still in early stages, and development o f more rapid and inexpensive markers from transcriptome and genome sequencing is expected to accelerate progress