Integer Linear Programming for Sequence Problems: A general approach to reduce the problem size

Sequence problems belong to the most challenging interdisciplinary topics of the actuality. They are ubiquitous in science and daily life and occur, for example, in form of DNA sequences encoding all information of an organism, as a text (natural or formal) or in form of a computer program. Therefore, sequence problems occur in many variations in computational biology (drug development), coding theory, data compression, quantitative and computational linguistics (e.g. machine translation). In recent years appeared some proposals to formulate sequence problems like the closest string problem (CSP) and the farthest string problem (FSP) as an Integer Linear Programming Problem (ILPP). In the present talk we present a general novel approach to reduce the size of the ILPP by grouping isomorphous columns of the string matrix together. The approach is of practical use, since the solution of sequence problems is very time consuming, in particular when the sequences are long.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Analysis of knockout/knockin mice that express a mutant FasL lacking the intracellular domain

Fas ligand (FasL; CD178; CD95L) is a type II transmembrane protein belonging to the tumour necrosis factor family; its binding to the Fas receptor (CD95; APO-1) triggers apoptosis in the receptor-bearing cell. Signalling through this pathway plays a pivotal role during the immune response and in immune system homeostasis. Similar to other TNF family members, the intracellular domain has been reported to transmit signals to the inside of the FasL-bearing cell (reverse signalling). Recently, we identified the proteases ADAM10 and SPPL2a as molecules important for the processing of FasL. Protease cleavage releases the intracellular domain, which then is able to translocate to the nucleus and to repress reporter gene activity. To study the physiological importance of FasL reverse signalling in vivo, we established knockout/knockin mice with a FasL deletion mutant that lacks the intracellular portion (FasLDeltaIntra). Co-culture experiments confirmed that the truncated FasL protein is still capable of inducing apoptosis in Fas-sensitive cells. Preliminary immune histochemistry data suggest that, in contrast to published data, the absence of the intracellular FasL domain does not alter the intracellular FasL localization in activated T cells. We are currently investigating signalling and proliferative capacities of T cells derived from homozygous FasLDeltaIntra mice to validate a co-stimulatory role of FasL reverse signalling

Phoneme Frequencies in Slovene (Text vs. Dictionary)

In this paper Slovene phoneme frequencies from a Slovene–German learner’s dictionary are analysed. The structure of the dictionary allows the determination of phoneme frequencies on two distinct linguistic levels: the level of dictionary (analysis of headwords) and the level of text (example sentences, illustrating a prototypical context of a given headword). By applying various statistical significance tests it can be shown that no significant differences between the rank-frequency distributions are observable. The same holds true for testing the differences, based on the repetition rate of phoneme frequencies on the dictionary and text levels. In contrast to this, only dichotomised data (by grouping them into vowels and consonants) show a significantly different frequency behaviour. Overall it can be shown that based on the given empirical observations, the conceptual importance and relevance of the levels of dictionary vs. text for quantitative phoneme studies has to be reconsidered and critically reflected in future studies

A functional yeast survival screen of tumor-derived cDNA libraries designed to identify anti-apoptotic mammalian oncogenes

Yeast cells can be killed upon expression of pro-apoptotic mammalian proteins. We have established a functional yeast survival screen that was used to isolate novel human anti-apoptotic genes overexpressed in treatment-resistant tumors. The screening of three different cDNA libraries prepared from metastatic melanoma, glioblastomas and leukemic blasts allowed for the identification of many yeast cell death-repressing cDNAs, including 28% of genes that are already known to inhibit apoptosis, 35% of genes upregulated in at least one tumor entity and 16% of genes described as both anti-apoptotic in function and upregulated in tumors. These results confirm the great potential of this screening tool to identify novel anti-apoptotic and tumor-relevant molecules. Three of the isolated candidate genes were further analyzed regarding their anti-apoptotic function in cell culture and their potential as a therapeutic target for molecular therapy. PAICS, an enzyme required for de novo purine biosynthesis, the long non-coding RNA MALAT1 and the MAST2 kinase are overexpressed in certain tumor entities and capable of suppressing apoptosis in human cells. Using a subcutaneous xenograft mouse model, we also demonstrated that glioblastoma tumor growth requires MAST2 expression. An additional advantage of the yeast survival screen is its universal applicability. By using various inducible pro-apoptotic killer proteins and screening the appropriate cDNA library prepared from normal or pathologic tissue of interest, the survival screen can be used to identify apoptosis inhibitors in many different systems

Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study

BACKGROUND: For virtually every patient with colorectal cancer (CRC), hematoxylin-eosin (HE)-stained tissue slides are available. These images contain quantitative information, which is not routinely used to objectively extract prognostic biomarkers. In the present study, we investigated whether deep convolutional neural networks (CNNs) can extract prognosticators directly from these widely available images. METHODS AND FINDINGS: We hand-delineated single-tissue regions in 86 CRC tissue slides, yielding more than 100,000 HE image patches, and used these to train a CNN by transfer learning, reaching a nine-class accuracy of >94% in an independent data set of 7,180 images from 25 CRC patients. With this tool, we performed automated tissue decomposition of representative multitissue HE images from 862 HE slides in 500 stage I-IV CRC patients in the The Cancer Genome Atlas (TCGA) cohort, a large international multicenter collection of CRC tissue. Based on the output neuron activations in the CNN, we calculated a "deep stroma score," which was an independent prognostic factor for overall survival (OS) in a multivariable Cox proportional hazard model (hazard ratio [HR] with 95% confidence interval [CI]: 1.99 [1.27-3.12], p = 0.0028), while in the same cohort, manual quantification of stromal areas and a gene expression signature of cancer-associated fibroblasts (CAFs) were only prognostic in specific tumor stages. We validated these findings in an independent cohort of 409 stage I-IV CRC patients from the "Darmkrebs: Chancen der Verhütung durch Screening" (DACHS) study who were recruited between 2003 and 2007 in multiple institutions in Germany. Again, the score was an independent prognostic factor for OS (HR 1.63 [1.14-2.33], p = 0.008), CRC-specific OS (HR 2.29 [1.5-3.48], p = 0.0004), and relapse-free survival (RFS; HR 1.92 [1.34-2.76], p = 0.0004). A prospective validation is required before this biomarker can be implemented in clinical workflows. CONCLUSIONS: In our retrospective study, we show that a CNN can assess the human tumor microenvironment and predict prognosis directly from histopathological images

Immunotherapy of Colorectal Cancer

It is known that the immune response, reflected by high T cell infiltrates in primary tumors and metastases, influences the clinical course of colorectal cancer (CRC). Therefore, immunotherapy concepts have been adapted from other tumor entities, which typically rely on the activation of T cells in the tumor microenvironment (e.g. blockade of the immune checkpoint molecules PD-1 and CTLA-4). However, most of the strategies using the approved checkpoint inhibitors and/or combination strategies have more or less failed to produce impressive results in early phase trials in CRC. Therefore, a number of novel targets for checkpoint inhibition are currently in early phase clinical testing (TIM-3, Lag-3, OX40, GITR, 4-1BB, CD40, CD70). A simple activation of infiltrating T cells will not, however, lead to a meaningful anti-tumor response without modulating the environmental factors in CRC. Thus, it is absolutely necessary to improve our understanding of the complex regulation of the tumor microenvironment in CRC to design individual combination treatments leading to effective immune control

Implementation of the Combined--Nonlinear Condensation Transformation

We discuss several applications of the recently proposed combined nonlinear-condensation transformation (CNCT) for the evaluation of slowly convergent, nonalternating series. These include certain statistical distributions which are of importance in linguistics, statistical-mechanics theory, and biophysics (statistical analysis of DNA sequences). We also discuss applications of the transformation in experimental mathematics, and we briefly expand on further applications in theoretical physics. Finally, we discuss a related Mathematica program for the computation of Lerch's transcendent.Comment: 23 pages, 1 table, 1 figure (Comput. Phys. Commun., in press

In silico SNP analysis of the breast cancer antigen NY-BR-1

Background: Breast cancer is one of the most common malignancies with increasing incidences every year and a leading cause of death among women. Although early stage breast cancer can be effectively treated, there are limited numbers of treatment options available for patients with advanced and metastatic disease. The novel breast cancer associated antigen NY-BR-1 was identified by SEREX analysis and is expressed in the majority (>70%) of breast tumors as well as metastases, in normal breast tissue, in testis and occasionally in prostate tissue. The biological function and regulation of NY-BR-1 is up to date unknown. Methods: We performed an in silico analysis on the genetic variations of the NY-BR-1 gene using data available in public SNP databases and the tools SIFT, Polyphen and Provean to find possible functional SNPs. Additionally, we considered the allele frequency of the found damaging SNPs and also analyzed data from an in-house sequencing project of 55 breast cancer samples for recurring SNPs, recorded in dbSNP. Results: Over 2800 SNPs are recorded in the dbSNP and NHLBI ESP databases for the NY-BR-1 gene. Of these, 65 (2.07%) are synonymous SNPs, 191 (6.09%) are non-synoymous SNPs, and 2430 (77.48%) are noncoding intronic SNPs. As a result, 69 non-synoymous SNPs were predicted to be damaging by at least two, and 16 SNPs were predicted as damaging by all three of the used tools. The SNPs rs200639888, rs367841401 and rs377750885 were categorized as highly damaging by all three tools. Eight damaging SNPs are located in the ankyrin repeat domain (ANK), a domain known for its frequent involvement in protein-protein interactions. No distinctive features could be observed in the allele frequency of the analyzed SNPs. Conclusion: Considering these results we expect to gain more insights into the variations of the NY-BR-1 gene and their possible impact on giving rise to splice variants and therefore influence the function of NY-BR-1 in healthy tissue as well as in breast cancer

The CD95 Receptor: Apoptosis Revisited

CD95 is the quintessential death receptor and, when it is bound by ligand, cells undergo apoptosis. Recent evidence suggests, however, that CD95 mediates not only apoptosis but also diverse nonapoptotic functions depending on the tissue and the conditions