Frequent genomic copy number gain and overexpression of GATA-6 in pancreatic carcinoma

Multiple genetic alterations are well recognized as contributing to pancreatic carcinogenesis, although the finding of recurrent copy number changes indicates additional targets remain to be found. The objective of this study was to identify novel targets of genetic alteration that contribute to pancreatic cancer development or progression. We used Representational Oligonucleotide Microarray Analysis (ROMA) to identify copy number changes in pancreatic cancer xenografts, and validated these findings using FISH, quantitative PCR, Western blotting and immunohistochemical labeling. With this approach, we identified a 0.36-Mb amplification at 18q11.2 containing two known genes, GATA-6 and cTAGE1. Using a cutoff value of 3.0 fold compared to haploid controls, copy number gain or amplification was confirmed in 4 of 42 (9.5%) pancreatic carcinomas analyzed. Combined genetic and transcriptional analyses showed consistent overexpression of GATA-6 in all carcinomas with 18q11.2 gain, as well as in the majority of pancreatic cancers examined (17 of 30 cancers, 56.7%) that did not have gain of this region. By contrast, overexpression of cTAGE1 was rare in these same cancers suggesting GATA-6 is the true target of this copy number increase. GATA-6 mRNA overexpression corresponded to robust nuclear protein expression in cancer cell lines and resected tissues consistent with its role as a transcription factor. Intense nuclear labeling was significantly increased in PanIN-3 lesions and infiltrating carcinomas compared to normal duct epithelium (p < 0.000001 and p < 0.003, respectively). Forced overexpression of GATA6 in MiaPaca2 cells resulted in increased proliferation and growth in soft-agar. Gain and overexpression of the development-related transcription factor GATA-6 may play an important and hitherto unrecognized role in pancreatic carcinogenesis

When Should One Substract Background Fluorescence in Two Color Microarrays?

Two color microarrays are a powerful tool for genomic analysis, but have noise components that make inferences regarding gene expression inefficient and potentially misleading. Background fluorescence,whether attributable to non-specific binding or other sources,is an important component of noise. The decision to subtract fluorescence surrounding spots of hybridization from spot fluorescence has been controversial, with no clear criteria for determining circumstances that may favor, or disfavor, background subtraction. While it is generally accepted that subtracting background reduces bias but increases variance in the estimates of the ratios of interest, no formal analysis of the bias-variance trade off of background subtraction has been undertaken. In this paper, we use simulation to systematically examine the bias-variance trade off under a variety of possible experimental conditions. Our simulation is based on data obtained from two self versus self microarray experiments and is free of distributional assumptions. Our results identify factors that are important for determining whether to background subtract, including the correlation of foreground to background intensity ratios. Using these results we develop recommendations for diagnostic visualizations that can help decisions about background subtraction

Cronkhite-Canada Syndrome: Gastric Involvement Diagnosed by MDCT

Chronkhite-Canada is a rare nonfamilial polyposis syndrome that usually presents as chronic malabsorption in adults. We present a case of a-73-year old woman with chronic gastrointestinal bleeding and malnutrition. On CT imaging she was found to have massive gastric polyps, which on biopsy was most consistent with Cronkhite-Canada syndrome

Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) remains a lethal disease with a 5-year survival of 4%. A key hallmark of PDAC is extensive stromal involvement, which makes capturing precise tumor-specific molecular information difficult. Here, we have overcome this problem by applying blind source separation to a diverse collection of PDAC gene expression microarray data, which includes primary, metastatic, and normal samples. By digitally separating tumor, stroma, and normal gene expression, we have identified and validated two tumor-specific subtypes including a “basal-like” subtype which has worse outcome, and is molecularly similar to basal tumors in bladder and breast cancer. Furthermore, we define “normal” and “activated” stromal subtypes which are independently prognostic. Our results provide new insight into the molecular composition of PDAC which may be used to tailor therapies or provide decision support in a clinical setting where the choice and timing of therapies is critical

IST Austria Technical Report

A comprehensive understanding of the clonal evolution of cancer is critical for understanding neoplasia. Genome-wide sequencing data enables evolutionary studies at unprecedented depth. However, classical phylogenetic methods often struggle with noisy sequencing data of impure DNA samples and fail to detect subclones that have different evolutionary trajectories. We have developed a tool, called Treeomics, that allows us to reconstruct the phylogeny of a cancer with commonly available sequencing technologies. Using Bayesian inference and Integer Linear Programming, robust phylogenies consistent with the biological processes underlying cancer evolution were obtained for pancreatic, ovarian, and prostate cancers. Furthermore, Treeomics correctly identified sequencing artifacts such as those resulting from low statistical power; nearly 7% of variants were misclassified by conventional statistical methods. These artifacts can skew phylogenies by creating illusory tumor heterogeneity among distinct samples. Importantly, we show that the evolutionary trees generated with Treeomics are mathematically optimal

Transoral laser surgery for laryngeal carcinoma: has Steiner achieved a genuine paradigm shift in oncological surgery?

Transoral laser microsurgery applies to the piecemeal removal of malignant tumours of the upper aerodigestive tract using the CO2 laser under the operating microscope. This method of surgery is being increasingly popularised as a single modality treatment of choice in early laryngeal cancers (T1 and T2) and occasionally in the more advanced forms of the disease (T3 and T4), predomi- nantly within the supraglottis. Thomas Kuhn, the American physicist turned philosopher and historian of science, coined the phrase ‘paradigm shift’ in his groundbreaking book The Structure of Scientific Revolutions. He argued that the arrival of the new and often incompatible idea forms the core of a new paradigm, the birth of an entirely new way of thinking. This article discusses whether Steiner and col- leagues truly brought about a paradigm shift in oncological surgery. By rejecting the principle of en block resection and by replacing it with the belief that not only is it oncologically safe to cut through the substance of the tumour but in doing so one can actually achieve better results, Steiner was able to truly revolutionise the man- agement of laryngeal cancer. Even though within this article the repercussions of his insight are limited to the upper aerodigestive tract oncological surgery, his willingness to question other peoples’ dogma makes his contribution truly a genuine paradigm shift

Cross-platform Comparison of Two Pancreatic Cancer Phenotypes

Model-based approaches for combining gene expression data from multiple high throughput platforms can be sensitive to technological artifacts when the number of samples in each platform is small. This paper proposes simple tools for quantifying concordance in a small study of pancreatic cancer cells lines with an emphasis on visualizations that uncover intra- and inter-platform variation. Using this approach, we identify several transcripts from the integrative analysis whose over-or under-expression in pancreatic cancer cell lines was validated by qPCR

Macrophage Ontogeny Underlies Differences in Tumor-Specific Education in Brain Malignancies.

Extensive transcriptional and ontogenetic diversity exists among normal tissue-resident macrophages, with unique transcriptional profiles endowing the cells with tissue-specific functions. However, it is unknown whether the origins of different macrophage populations affect their roles in malignancy. Given potential artifacts associated with irradiation-based lineage tracing, it remains unclear if bone-marrow-derived macrophages (BMDMs) are present in tumors of the brain, a tissue with no homeostatic involvement of BMDMs. Here, we employed multiple models of murine brain malignancy and genetic lineage tracing to demonstrate that BMDMs are abundant in primary and metastatic brain tumors. Our data indicate that distinct transcriptional networks in brain-resident microglia and recruited BMDMs are associated with tumor-mediated education yet are also influenced by chromatin landscapes established before tumor initiation. Furthermore, we demonstrate that microglia specifically repress Itga4 (CD49D), enabling its utility as a discriminatory marker between microglia and BMDMs in primary and metastatic disease in mouse and human

Interrogation of the Microenvironmental Landscape in Brain Tumors Reveals Disease-Specific Alterations of Immune Cells

Brain malignancies encompass a range of primary and metastatic cancers, including low-grade and high-grade gliomas and brain metastases (BrMs) originating from diverse extracranial tumors. Our understanding of the brain tumor microenvironment (TME) remains limited, and it is unknown whether it is sculpted differentially by primary versus metastatic disease. We therefore comprehensively analyzed the brain TME landscape via flow cytometry, RNA sequencing, protein arrays, culture assays, and spatial tissue characterization. This revealed disease-specific enrichment of immune cells with pronounced differences in proportional abundance of tissue-resident microglia, infiltrating monocyte-derived macrophages, neutrophils, and T cells. These integrated analyses also uncovered multifaceted immune cell activation within brain malignancies entailing converging transcriptional trajectories while maintaining disease- and cell-type-specific programs. Given the interest in developing TME-targeted therapies for brain malignancies, this comprehensive resource of the immune landscape offers insights into possible strategies to overcome tumor-supporting TME properties and instead harness the TME to fight cancer