Regulation of mammary gland branching morphogenesis by the extracellular matrix and its remodeling enzymes.

A considerable body of research indicates that mammary gland branching morphogenesis is dependent, in part, on the extracellular matrix (ECM), ECM-receptors, such as integrins and other ECM receptors, and ECM-degrading enzymes, including matrix metalloproteinases (MMPs) and their inhibitors, tissue inhibitors of metalloproteinases (TIMPs). There is some evidence that these ECM cues affect one or more of the following processes: cell survival, polarity, proliferation, differentiation, adhesion, and migration. Both three-dimensional culture models and genetic manipulations of the mouse mammary gland have been used to study the signaling pathways that affect these processes. However, the precise mechanisms of ECM-directed mammary morphogenesis are not well understood. Mammary morphogenesis involves epithelial 'invasion' of adipose tissue, a process akin to invasion by breast cancer cells, although the former is a highly regulated developmental process. How these morphogenic pathways are integrated in the normal gland and how they become dysregulated and subverted in the progression of breast cancer also remain largely unanswered questions

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

A computational analysis of the dynamic roles of talin, Dok1, and PIPKI for integrin activation

Integrin signaling regulates cell migration and plays a pivotal role in developmental processes and cancer metastasis. Integrin signaling has been studied extensively and much data is available on pathway components and interactions. Yet the data is fragmented and an integrated model is missing. We use a rule-based modeling approach to integrate available data and test biological hypotheses regarding the role of talin, Dok1 and PIPKI in integrin activation. The detailed biochemical characterization of integrin signaling provides us with measured values for most of the kinetics parameters. However, measurements are not fully accurate and the cellular concentrations of signaling proteins are largely unknown and expected to vary substantially across different cellular conditions. By sampling model behaviors over the physiologically realistic parameter range we find that the model exhibits only two different qualitative behaviours and these depend mainly on the relative protein concentrations, which offers a powerful point of control to the cell. Our study highlights the necessity to characterize model behavior not for a single parameter optimum, but to identify parameter sets that characterize different signaling modes

Comparison of Gene Expression Profiles in Chromate Transformed BEAS-2B Cells

Hexavalent chromium [Cr(VI)] is a potent human carcinogen. Occupational exposure has been associated with increased risk of respiratory cancer. Multiple mechanisms have been shown to contribute to Cr(VI) induced carcinogenesis, including DNA damage, genomic instability, and epigenetic modulation, however, the molecular mechanism and downstream genes mediating chromium's carcinogenicity remain to be elucidated.We established chromate transformed cell lines by chronic exposure of normal human bronchial epithelial BEAS-2B cells to low doses of Cr(VI) followed by anchorage-independent growth. These transformed cell lines not only exhibited consistent morphological changes but also acquired altered and distinct gene expression patterns compared with normal BEAS-2B cells and control cell lines (untreated) that arose spontaneously in soft agar. Interestingly, the gene expression profiles of six Cr(VI) transformed cell lines were remarkably similar to each other yet differed significantly from that of either control cell lines or normal BEAS-2B cells. A total of 409 differentially expressed genes were identified in Cr(VI) transformed cells compared to control cells. Genes related to cell-to-cell junction were upregulated in all Cr(VI) transformed cells, while genes associated with the interaction between cells and their extracellular matrices were down-regulated. Additionally, expression of genes involved in cell proliferation and apoptosis were also changed.This study is the first to report gene expression profiling of Cr(VI) transformed cells. The gene expression changes across individual chromate exposed clones were remarkably similar to each other but differed significantly from the gene expression found in anchorage-independent clones that arose spontaneously. Our analysis identified many novel gene expression changes that may contribute to chromate induced cell transformation, and collectively this type of information will provide a better understanding of the mechanism underlying chromate carcinogenicity

Controlling cell behavior through the design of polymer surfaces

Polymers have gained a remarkable place in the biomedical fi eld as materials for the fabrication of various devices and for tissue engineering applications. The initial acceptance or rejection of an implantable device is dictated by the crosstalk of the material surface with the bioentities present in the physiological environment. Advances in microfabrication and nanotechnology offer new tools to investigate the complex signaling cascade induced by the components of the extracellular matrix and consequently allow cellular responses to be tailored through the mimicking of some elements of the signaling paths. Patterning methods and selective chemical modifi cation schemes at different length scales can provide biocompatible surfaces that control cellular interactions on the micrometer and sub-micrometer scales on which cells are organized. In this review, the potential of chemically and topographically structured micro- and nanopolymer surfaces are discussed in hopes of a better understanding of cell–biomaterial interactions, including the recent use of biomimetic approaches or stimuli-responsive macromolecules. Additionally, the focus will be on how the knowledge obtained using these surfaces can be incorporated to design biocompatible materials for various biomedical applications, such as tissue engineering, implants, cell-based biosensors, diagnostic systems, and basic cell biology. The review focusses on the research carried out during the last decade.The research leading to these results has received partial funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. NMP4-SL-2009-229292 and by the FCT projects PTDC/FIS/68517/2006, PTDC/QUI/69263/2006, PTDC/FIS/68209/2006, and PTDC/QUI/68804/2006

Quantitative Deep Sequencing Reveals Dynamic HIV-1 Escape and Large Population Shifts during CCR5 Antagonist Therapy In Vivo

High-throughput sequencing platforms provide an approach for detecting rare HIV-1 variants and documenting more fully quasispecies diversity. We applied this technology to the V3 loop-coding region of env in samples collected from 4 chronically HIV-infected subjects in whom CCR5 antagonist (vicriviroc [VVC]) therapy failed. Between 25,000–140,000 amplified sequences were obtained per sample. Profound baseline V3 loop sequence heterogeneity existed; predicted CXCR4-using populations were identified in a largely CCR5-using population. The V3 loop forms associated with subsequent virologic failure, either through CXCR4 use or the emergence of high-level VVC resistance, were present as minor variants at 0.8–2.8% of baseline samples. Extreme, rapid shifts in population frequencies toward these forms occurred, and deep sequencing provided a detailed view of the rapid evolutionary impact of VVC selection. Greater V3 diversity was observed post-selection. This previously unreported degree of V3 loop sequence diversity has implications for viral pathogenesis, vaccine design, and the optimal use of HIV-1 CCR5 antagonists