Scanning thermal microscopy using nanofabricated probes

Novel atomic force microscope (AFM) probes with integrated thin film thermal sensors are presented. Silicon micromachining and high resolution electron beam lithography (EBL) have been used to make batch fabricated, functionalised AFM probes. The AFM tips, situated at the ends of Si3N4 cantilevers, are shaped either as truncated pyramids or sharp triangular asperites. The former gives good thermalisation of the sensor to the specimen for flat specimens whereas the latter gives improved access to highly topographic specimens. Tip radii for the different probes are 1 m and 50 nm respectively. A variety of metal structures have been deposited on the tips using EBL and lift-off to form Au/Pd thermocouples and Pd resistance thermometer/heaters. Sensor dimensions down to 35 nm have been demonstrated. In the case of the sharp triangular tips, holes were etched into parts of the cantilever in order to provide self alignment of the sensor to the tip. On the pyramidal tips it has been shown that multiple sensors can be made on a single tip with good definition and matching between sensors. A conventional AFM was constructed in order to test the micromachined thermal probes. During scans of a photothermal test specimen using improved access thermocouple probes, 80 nm period metal gratings were thermally resolved. This is equivalent to a thermal lateral resolution of 40 nm. Pyramidal tips with a resistance thermometer/heater, which were made for the microscopy and analysis of polymers, have been showed by others to produce high resolution thermal conductivity images. The probes have also been shown to be capable of locally heating a polymer specimen and thermomechanically measuring phase changes in small volumes of material. Also presented here is a study of scanning thermal microscopy of semiconductor structures using a commercial AFM. Included are scans of several specimens using both commercial andthe new micromachined probes. Subsurface images of voids buried under a SiO2 passivation layer were taken. It is shown that contrast caused by thermal conductivity differences in the specimen may be detected at a depth of over 200 nm

OncoLog Volume 53, Number 03, March 2008

In Search of the Answer DiaLog: Mapping the Cancer Genome, by Gordon Mills, MD, PhD, Director, Kleberg Center for Molecular Markers, Chair, Department of Systems Biology House Call: The Basics of Biopsieshttps://openworks.mdanderson.org/oncolog/1168/thumbnail.jp

OncoLog Volume 45, Number 05, May 2000

Early Detection of Melanoma Spread May Increase Survival Benefits of Adjuvant Therapy No Easy Answers: Women at Increased Risk for Breast Cancer Face Difficult Choices DiaLog: Understanding Risk: A Prerequisite for Making Informed Decisions, by Gordon B. Mills, MD, PhD, Chairman, Department of Molecular Therapeutics House Call: Looking for Trouble: How to Spot Signs of Melanoma Protocols: Melanoma Clinical Trials Biochemotherapy Means Hope for Patients with Advanced Melanomahttps://openworks.mdanderson.org/oncolog/1085/thumbnail.jp

0103-72.6: A New Oxygen-Rich Supernova Remnant in the Small Magellanic Cloud

0103$-$72.6, the second brightest X-ray supernova remnant (SNR) in the Small Magellanic Cloud (SMC), has been observed with the {\it Chandra X-Ray Observatory}. Our {\it Chandra} observation unambiguously resolves the X-ray emission into a nearly complete, remarkably circular shell surrounding bright clumpy emission in the center of the remnant. The observed X-ray spectrum for the central region is evidently dominated by emission from reverse shock-heated metal-rich ejecta. Elemental abundances in this ejecta material are particularly enhanced in oxygen and neon, while less prominent in the heavier elements Si, S, and Fe. We thus propose that 0103$-$72.6 is a new ``oxygen-rich'' SNR, making it only the second member of the class in the SMC. The outer shell is the limb-brightened, soft X-ray emission from the swept-up SMC interstellar medium. The presence of O-rich ejecta and the SNR's location within an H{\small II} region attest to a massive star core-collapse origin for 0103$-$72.6. The elemental abundance ratios derived from the ejecta suggest an $\sim$18 M$_{\odot}$ progenitor star.Comment: 6 pages (ApJ emulator format), including 5 figures and 2 tables. For high quality Figs.1,2, & 3, contact [email protected]. Accepted by the ApJ Letter

Prognostic relevance of acquired uniparental disomy in serous ovarian cancer

BACKGROUND: Acquired uniparental disomy (aUPD) can lead to homozygosity for tumor suppressor genes or oncogenes. Our purpose is to determine the frequency and profile aUPD regions in serous ovarian cancer (SOC) and investigated the association of aUPD with clinical features and patient outcomes.METHODS: We analyzed single nucleotide polymorphism (SNP) array-based genotyping data on 532 SOC specimens from The Cancer Genome Atlas database to identify aUPD regions. Cox univariate regression and Cox multivariate proportional hazards analyses were performed for survival analysis.RESULTS: We found that 94.7% of SOC samples harbored aUPD; the most common aUPD regions were in chromosomes 17q (76.7%), 17p (39.7%), and 13q (38.3%). In Cox univariate regression analysis, two independent regions of aUPD on chromosome 17q (A and C), and whole-chromosome aUPD were associated with shorter overall survival (OS), and five regions on chromosome 17q (A, D-G) and BRCA1 were associated with recurrence-free survival time. In Cox multivariable proportional hazards analysis, whole-chromosome aUPD was associated with shorter OS. One region of aUPD on chromosome 22q (B) was associated with unilateral disease. A statistically significant association was found between aUPD at TP53 loci and homozygous mutation of TP53 (p < 0.0001).CONCLUSIONS: aUPD is a common event and some recurrent loci are associated with a poor outcome for patients with serous ovarian cancer

Systems Biology Approaches to Decoding the Genome of Liver Cancer

Molecular classification of cancers has been significantly improved patient outcomes through the implementation of treatment protocols tailored to the abnormalities present in each patient's cancer cells. Breast cancer represents the poster child with marked improvements in outcome occurring due to the implementation of targeted therapies for estrogen receptor or human epidermal growth factor receptor-2 positive breast cancers. Important subtypes with characteristic molecular features as potential therapeutic targets are likely to exist for all tumor lineages including hepatocellular carcinoma (HCC) but have yet to be discovered and validated as targets. Because each tumor accumulates hundreds or thousands of genomic and epigenetic alterations of critical genes, it is challenging to identify and validate candidate tumor aberrations as therapeutic targets or biomarkers that predict prognosis or response to therapy. Therefore, there is an urgent need to devise new experimental and analytical strategies to overcome this problem. Systems biology approaches integrating multiple data sets and technologies analyzing patient tissues holds great promise for the identification of novel therapeutic targets and linked predictive biomarkers allowing implementation of personalized medicine for HCC patients

Molecular heterogeneity at the network level: high-dimensional testing, clustering and a TCGA case study.

MOTIVATION: Molecular pathways and networks play a key role in basic and disease biology. An emerging notion is that networks encoding patterns of molecular interplay may themselves differ between contexts, such as cell type, tissue or disease (sub)type. However, while statistical testing of differences in mean expression levels has been extensively studied, testing of network differences remains challenging. Furthermore, since network differences could provide important and biologically interpretable information to identify molecular subgroups, there is a need to consider the unsupervised task of learning subgroups and networks that define them. This is a nontrivial clustering problem, with neither subgroups nor subgroup-specific networks known at the outset. RESULTS: We leverage recent ideas from high-dimensional statistics for testing and clustering in the network biology setting. The methods we describe can be applied directly to most continuous molecular measurements and networks do not need to be specified beforehand. We illustrate the ideas and methods in a case study using protein data from The Cancer Genome Atlas (TCGA). This provides evidence that patterns of interplay between signalling proteins differ significantly between cancer types. Furthermore, we show how the proposed approaches can be used to learn subtypes and the molecular networks that define them. AVAILABILITY AND IMPLEMENTATION: As the Bioconductor package nethet. CONTACT: [email protected] or [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

Analysis of phosphatases in ER-negative breast cancers identifies DUSP4 as a critical regulator of growth and invasion.

Estrogen receptor (ER)-negative cancers have a poor prognosis, and few targeted therapies are available for their treatment. Our previous analyses have identified potential kinase targets critical for the growth of ER-negative, progesterone receptor (PR)-negative and HER2-negative, or "triple-negative" breast cancer (TNBC). Because phosphatases regulate the function of kinase signaling pathways, in this study, we investigated whether phosphatases are also differentially expressed in ER-negative compared to those in ER-positive breast cancers. We compared RNA expression in 98 human breast cancers (56 ER-positive and 42 ER-negative) to identify phosphatases differentially expressed in ER-negative compared to those in ER-positive breast cancers. We then examined the effects of one selected phosphatase, dual specificity phosphatase 4 (DUSP4), on proliferation, cell growth, migration and invasion, and on signaling pathways using protein microarray analyses of 172 proteins, including phosphoproteins. We identified 48 phosphatase genes are significantly differentially expressed in ER-negative compared to those in ER-positive breast tumors. We discovered that 31 phosphatases were more highly expressed, while 11 were underexpressed specifically in ER-negative breast cancers. The DUSP4 gene is underexpressed in ER-negative breast cancer and is deleted in approximately 50&nbsp;% of breast cancers. Induced DUSP4 expression suppresses both in vitro and in vivo growths of breast cancer cells. Our studies show that induced DUSP4 expression blocks the cell cycle at the G1/S checkpoint; inhibits ERK1/2, p38, JNK1, RB, and NFkB p65 phosphorylation; and inhibits invasiveness of TNBC cells. These results suggest that that DUSP4 is a critical regulator of the growth and invasion of triple-negative breast cancer cells

Polymorphisms in the SULF1 gene are associated with early age of onset and survival of ovarian cancer

<p>Abstract</p> <p>Background</p> <p>SULF1 (sulfatase 1) selectively removes the 6-O-sulphate group from heparan sulfate, changing the binding sites for extracellular growth factors. <it>SULF1 </it>expression has been reported to be decreased in various cancers, including ovarian cancer. We hypothesized that single nucleotide polymorphisms (SNPs) of <it>SULF1 </it>would impact clinicopathologic characteristics.</p> <p>Methods</p> <p>We genotyped five common (minor allele frequency>0.05) regulatory SNPs with predicted functionalities (rs2623047 G>A, rs13264163 A>G, rs6990375 G>A, rs3802278 G>A, and rs3087714 C>T) in 168 patients with primary epithelial ovarian cancer, using the polymerase chain reaction-restriction fragment length polymorphism method.</p> <p>Results</p> <p>We found that rs2623047 G>A was significantly associated with an early age of onset of ovarian cancer in the G allele dose-response manner (<it>P </it>= 0.027; <it>P_trend</it>= 0.007) and that rs2623047 GG/GA genotypes were associated with longer progression-free survival; rs6990375 G>A was also associated with the early age of onset in the A allele dose-response manner (<it>P </it>= 0.013; <it>P_trend</it>= 0.009). The significant differences in age of disease onset persisted among carriers of haplotypes of rs2623047 and rs6990375 (<it>P </it>= 0.014; <it>P_trend</it>= 0.004). In luciferase reporter gene assays, rs2623047 G allele showed a slightly higher promoter activity than the A allele in the SKOV3 tumorigenic cell line.</p> <p>Conclusions</p> <p>These findings suggest that genetic variations in <it>SULF1 </it>may play a role in ovarian cancer onset and prognosis. Further studies with large sample sizes and of the mechanistic relevance of <it>SULF1 </it>SNPs are warranted.</p

An efficient procedure for protein extraction from formalin-fixed, paraffin-embedded tissues for reverse phase protein arrays

INTRODUCTION: Protein extraction from formalin-fixed paraffin-embedded (FFPE) tissues is challenging due to extensive molecular crosslinking that occurs upon formalin fixation. Reverse-phase protein array (RPPA) is a high-throughput technology, which can detect changes in protein levels and protein functionality in numerous tissue and cell sources. It has been used to evaluate protein expression mainly in frozen preparations or FFPE-based studies of limited scope. Reproducibility and reliability of the technique in FFPE samples has not yet been demonstrated extensively. We developed and optimized an efficient and reproducible procedure for extraction of proteins from FFPE cells and xenografts, and then applied the method to FFPE patient tissues and evaluated its performance on RPPA. RESULTS: Fresh frozen and FFPE preparations from cell lines, xenografts and breast cancer and renal tissues were included in the study. Serial FFPE cell or xenograft sections were deparaffinized and extracted by six different protein extraction protocols. The yield and level of protein degradation were evaluated by SDS-PAGE and Western Blots. The most efficient protocol was used to prepare protein lysates from breast cancer and renal tissues, which were subsequently subjected to RPPA. Reproducibility was evaluated and Spearman correlation was calculated between matching fresh frozen and FFPE samples. The most effective approach from six protein extraction protocols tested enabled efficient extraction of immunoreactive protein from cell line, breast cancer and renal tissue sample sets. 85% of the total of 169 markers tested on RPPA demonstrated significant correlation between FFPE and frozen preparations (p < 0.05) in at least one cell or tissue type, with only 23 markers common in all three sample sets. In addition, FFPE preparations yielded biologically meaningful observations related to pathway signaling status in cell lines, and classification of renal tissues. CONCLUSIONS: With optimized protein extraction methods, FFPE tissues can be a valuable source in generating reproducible and biologically relevant proteomic profiles using RPPA, with specific marker performance varying according to tissue type