Breast cancer patients with the same stage of disease can have markedly different treatment responses and overall outcome. The strongest predictors for metastases (for example, lymph node status and histological grade) fail to classify accurately breast tumours according to their clinical behaviour. Chemotherapy or hormonal therapy reduces the risk of distant metastases by approximately one-third; however, 70-80% of patients receiving this treatment would have survived without it. None of the signatures of breast cancer gene expression reported to date allow for patient-tailored therapy strategies. Here we used DNA microarray analysis on primary breast tumours of 117 young patients, and applied supervised classification to identify a gene expression signature strongly predictive of a short interval to distant metastases ('poor prognosis' signature) in patients without tumour cells in local lymph nodes at diagnosis (lymph node negative). In addition, we established a signature that identifies tumours of BRCA1 carriers. The poor prognosis signature consists of genes regulating cell cycle, invasion, metastasis and angiogenesis. This gene expression profile will outperform all currently used clinical parameters in predicting disease outcome. Our findings provide a strategy to select patients who would benefit from adjuvant therapy.

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Gene expression profiling predicts clinical outcome of breast cancer

Since the publication of the American Association for the Study of Liver Diseases (AASLD) practice guidelines on the management of hepatocellular carcinoma (HCC) in 2005, new information has emerged that requires that the guidelines be updated. The full version of the new guidelines is available on the AASLD Web site at http://www.aasld.org/practiceguidelines/ Documents/Bookmarked%20Practice%20Guidelines/ HCCUpdate2010.pdf. Here, we briefly describe only new or changed recommendations.

/pdf/aasld-practice-guideline-management-of-hepatocellular-51bocalv0r.pdf

AASLD PRACTICE GUIDELINE Management of Hepatocellular Carcinoma: An Update

Background A more accurate means of prognostication in breast cancer will improve the selection of patients for adjuvant systemic therapy. Methods Using microarray analysis to evaluate our previously established 70-gene prognosis profile, we classified a series of 295 consecutive patients with primary breast carcinomas as having a gene-expression signature associated with either a poor prognosis or a good prognosis. All patients had stage I or II breast cancer and were younger than 53 years old; 151 had lymph-node–negative disease, and 144 had lymph-node–positive disease. We evaluated the predictive power of the prognosis profile using univariable and multivariable statistical analyses. Results Among the 295 patients, 180 had a poor-prognosis signature and 115 had a good-prognosis signature, and the mean (±SE) overall 10-year survival rates were 54.6±4.4 percent and 94.5±2.6 percent, respectively. At 10 years, the probability of remaining free of distant metastases was 50.6±4.5 percent in the group with a...

/pdf/a-gene-expression-signature-as-a-predictor-of-survival-in-1f6irz2ok6.pdf

A Gene-Expression Signature as a Predictor of Survival in Breast Cancer

Data analysis plays an indispensable role for understanding various phenomena. Cluster analysis, primitive exploration with little or no prior knowledge, consists of research developed across a wide variety of communities. The diversity, on one hand, equips us with many tools. On the other hand, the profusion of options causes confusion. We survey clustering algorithms for data sets appearing in statistics, computer science, and machine learning, and illustrate their applications in some benchmark data sets, the traveling salesman problem, and bioinformatics, a new field attracting intensive efforts. Several tightly related topics, proximity measure, and cluster validation, are also discussed.

/pdf/survey-of-clustering-algorithms-6zezqhbjyo.pdf

Survey of clustering algorithms

https://aasldpubs.onlinelibrary.wiley.com/doi/pdf/10.1002/hep.20933

Management of hepatocellular carcinoma.

MicroRNA-200c-141 and ∆Np63 are required for breast epithelial differentiation and branching morphogenesis.

Summary: Array Close Information Database is an online database for information about microarray cDNA clones. For each clone, the database contents include assigned UniGene cluster(s), location in the full-length transcript, assigned gene ontology terms and position in the genome assembly.

Availability: http://bioinfo.thep.lu.se/acid.html

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ACID: a database for microarray clone information

Transverse and longitudinal Bose-Einstein correlations

The neural transcription factor SOX11 is present at specific stages during embryo development with a very restricted expression in adult tissue, indicating precise regulation of transcription. SOX11 is strongly up-regulated in some malignancies and have a functional role in tumorgenesis. With the aim to explore differences in epigenetic regulation of SOX11 expression in normal versus neoplastic cells, we investigated methylation and histone modifications related to the SOX11 promoter and the possibility to induce re-expression using histone deacetylase (HDAC) or EZH2 inhibitors.

/pdf/dna-methylation-and-histone-modifications-regulate-sox11-84t3uh5pu2.pdf

DNA methylation and histone modifications regulate SOX11 expression in lymphoid and solid cancer cells

We discuss what happens at the end of the QCD cascades. We show that, with just a few reasonable assumptions, the emission of soft gluons is constrained to produce an ordered field in the form of a helix. We describe how to modify the Lund fragmentation scheme in order to fragment such a field. Our modified fragmentation scheme yields results which are consistent with current experimental measurements, but predicts at least one signature which should be observable.

/pdf/is-there-screwiness-at-the-end-of-the-qcd-cascades-4pfs23w0bm.pdf

Markus Ringnér

Papers

MicroRNA-200c-141 and ∆Np63 are required for breast epithelial differentiation and branching morphogenesis.

ACID: a database for microarray clone information

Transverse and longitudinal Bose-Einstein correlations

DNA methylation and histone modifications regulate SOX11 expression in lymphoid and solid cancer cells

Is there screwiness at the end of the QCD cascades