Global analyses of RNA expression levels are useful for classifying genes and overall phenotypes. Often these classification problems are linked, and one wants to find "marker genes" that are differentially expressed in particular sets of "conditions." We have developed a method that simultaneously clusters genes and conditions, finding distinctive "checkerboard" patterns in matrices of gene expression data, if they exist. In a cancer context, these checkerboards correspond to genes that are markedly up-or downregulated in patients with particular types of tumors. Our method, spectral biclustering, is based on the observation that checkerboard structures in matrices of expression data can be found in eigenvectors corresponding to characteristic expression patterns across genes or conditions. In addition, these eigenvectors can be readily identified by commonly used linear algebra approaches, in particular the singular value decomposition (SVD), coupled with closely integrated normalization steps. We present a number of variants of the approach, depending on whether the normalization over genes and conditions is done independently or in a coupled fashion. We then apply spectral biclustering to a selection of publicly available cancer expression data sets, and examine the degree to which the approach is able to identify checkerboard structures. Furthermore, we compare the performance of our biclustering methods against a number of reasonable benchmarks (e.g., direct application of SVD or normalized cuts to raw data).

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The miRNA participates in a variety of biologic processes, and dysregulation of miRNA is associated with malignant transformation. In this study, we determined specific profile of miRNA associated with oral cancer by using miRNA array screening method. There were 23 miRNAs found with considerably differential expressions between six oral cancer cell lines and five lines of normal oral keratinocytes, in which, 10 miRNAs showed the highest significant difference after independent examination by reverse transcription quantitative PCR. Eight molecules were upregulated, miR-10b, miR-196a, miR-196b, miR-582-5p, miR15b, miR-301, miR-148b, and miR-128a, and two molecules, miR-503 and miR-31, were downregulated. The most upregulated miR-10b was further examined, and its functions were characterized in two oral cancer cell lines. The miR-10b actively promotes cell migration (2.6-to 3.6-fold) and invasion (1.7-to 1.9-fold) but has minimal effect on cell growth or chemo-/radiosensitivity. Furthermore, miR-10b was considerably elevated in the plasma of xenografted tumor mice (20-fold). This upregulation of miR-10b in plasma was further shown in the patients with oral cancer [P < 0.0001, area under curve (AUC) ¼ 0.932] and precancer lesions (P < 0.0001, AUC ¼ 0.967), suggesting that miR-10b possesses a high potential to discriminate the normal subjects. In conclusion, we have identified at least 10 miRNAs significantly associated with oral cancer, including the most elevated miR-10b. The miR-10b actively participates in cancer formation by promoting cell migration and invasion. Our study using clinical samples suggests that plasma miR-10b has high potential as an early detection marker for oral cancer. Cancer Prev Res; 5(4); 665-74. Ó2012 AACR. Impact of this paper:1. miRNA signature of oral cancer was determined. 2. The oncogenic function of miR-10b in oral cancer was first demonstrated. 3. The potential of miR-10b as a circulating biomarker for the early detection of oral cancer was presented.

Conditional probability distributions seem to have a bad reputation when it comes to rigorous treatment of conditioning. Technical arguments are published as manipulations of Radon±Nikodym derivatives, although we all secretly perform heuristic calculations using elementary de®nitions of conditional probabilities. In print, measurability and averaging properties substitute for intuitive ideas about random variables behaving like constants given particular conditioning information.One way to engage in rigorous, guilt-free manipulation of conditional distributions is to treat them as disintegrating measuresÐfamilies of probability measures concentrating on the level sets of a conditioning statistic. In this paper we present a little theory and a range of examplesÐfrom EM algorithms and the Neyman factorization, through Bayes theory and marginalization paradoxesÐto suggest that disintegrations have both intuitive appeal and the rigor needed for many problems in mathematical statistics.

BackgroundTumor cell fusion with motile bone marrow-derived cells (BMDCs) has long been posited as a mechanism for cancer metastasis. While there is much support for this from cell culture and animal studies, it has yet to be confirmed in human cancer, as tumor and marrow-derived cells from the same patient cannot be easily distinguished genetically.MethodsWe carried out genotyping of a metastatic melanoma to the brain that arose following allogeneic bone-marrow transplantation (BMT), using forensic short tandem repeat (STR) length-polymorphisms to distinguish donor and patient genomes. Tumor cells were isolated free of leucocytes by laser microdissection, and tumor and pre-transplant blood lymphocyte DNAs were analyzed for donor and patient alleles at 14 autosomal STR loci and the sex chromosomes.ResultsAll alleles in the donor and patient pre-BMT lymphocytes were found in tumor cells. The alleles showed disproportionate relative abundances in similar patterns throughout the tumor, indicating the tumor was initiated by a clonal fusion event.ConclusionsOur results strongly support fusion between a BMDC and a tumor cell playing a role in the origin of this metastasis. Depending on the frequency of such events, the findings could have important implications for understanding the generation of metastases, including the origins of tumor initiating cells and the cancer epigenome.

Background-Autism Spectrum Disorders (ASD) are neurodevelopmental disorders of complex etiology, with a recognized substantial contribution of heterogeneous genetic factors; one of the core features of ASD is a lack of affiliative behaviors.

Previous studies have shown that total lesion glycolysis (TLG) may serve as a prognostic indicator in oropharyngeal squamous cell carcinoma (OPSCC). We sought to investigate whether the textural features of pretreatment 18 F-FDG PET/CT images can provide any additional prognostic information over TLG and clinical staging in patients with advanced T-stage OPSCC. Methods: We retrospectively analyzed the pretreatment 18 F-FDG PET/CT images of 70 patients with advanced T-stage OPSCC who had completed concurrent chemoradiotherapy, bioradiotherapy, or radiotherapy with curative intent. All of the patients had data on human papillomavirus (HPV) infection and were followed up for at least 24 mo or until death. A standardized uptake value (SUV) of 2.5 was taken as a cutoff for tumor boundary. The textural features of pretreatment 18 F-FDG PET/CT images were extracted from histogram analysis (SUV variance and SUV entropy), normalized gray-level cooccurrence matrix (uniformity, entropy, dissimilarity, contrast, homogeneity, inverse different moment, and correlation), and neighborhood gray-tone difference matrix (coarseness, contrast, busyness, complexity, and strength). Receiver-operating-characteristic curves were used to identify the optimal cutoff values for the textural features and TLG. Results: Thirteen patients were HPV-positive. Multivariate Cox regression analysis showed that age, tumor TLG, and uniformity were independently associated with progression-free survival (PFS) and disease-specific survival (DSS). TLG, uniformity, and HPV positivity were significantly associated with overall survival (OS). A prognostic scoring system based on TLG and uniformity was derived. Patients who presented with TLG . 121.9 g and uniformity # 0.138 experienced significantly worse PFS, DSS, and OS rates than those without (P , 0.001, , 0.001, and 0.002, respectively). Patients with TLG . 121.9 g or uniformity # 0.138 were further divided according to age, and different PFS and DSS were observed. Conclusion: Uniformity extracted from the normalized gray-level cooccurrence matrix represents an independent prognostic predictor in patients with advanced T-stage OPSCC. A scoring system was developed and may serve as a risk-stratification strategy for guiding therapy.