Gene expression profiling in aggressive digital papillary adenocarcinoma sheds light on the architecture of a rare sweat gland carcinoma.

BACKGROUND: Sweat gland carcinomas are rare cutaneous adnexal malignancies. Aggressive digital papillary adenocarcinoma (ADPA) represents a very rare subentity, thought to arise almost exclusively from the sweat glands of the fingers and toes. The aetiology of sweat gland carcinomas and ADPA is largely unknown. ADPAs are most likely driven by somatic mutations. However, somatic mutation patterns are largely unexplored, creating barriers to the development of effective therapeutic approaches to the treatment of ADPA. OBJECTIVES: To investigate the transcriptome profile of ADPA using a sample of eight formalin-fixed, paraffin-embedded tissue samples of ADPA and healthy control tissue. METHODS: Transcriptome profiling was performed using the Affymetrix PrimeView Human Gene Expression Microarray and findings were validated via reverse transcription of RNA and real-time quantitative polymerase chain reaction. RESULTS: Transcriptome analyses showed increased tumour expression of 2266 genes, with significant involvement of cell cycle, ribosomal and crucial cancer pathways. Our results point to tumour overexpression of FGFR2 (P = 0·001). CONCLUSIONS: The results indicate the involvement of crucial oncogenic driver pathways, highlighting cell cycle and ribosomal pathways in the aetiology of ADPA. Suggested tumour overexpression of FGFR2 raises the hope that targeting the fibroblast growth factor (FGF)/FGF receptor axis might be a promising treatment for ADPA and probably for the overall group of sweat gland carcinomas.

Pluripotent stem cells: induction and self-renewal.

Pluripotent stem cells (PSCs) lie at the heart of modern regenerative medicine due to their properties of unlimited self-renewal in vitro and their ability to differentiate into cell types representative of the three embryonic germ layers-mesoderm, ectoderm and endoderm. The derivation of induced PSCs bypasses ethical concerns associated with the use of human embryonic stem cells and also enables personalized cell-based therapies. To exploit their regenerative potential, it is essential to have a firm understanding of the molecular processes associated with their induction from somatic cells. This understanding serves two purposes: first, to enable efficient, reliable and cost-effective production of excellent quality induced PSCs and, second, to enable the derivation of safe, good manufacturing practice-grade transplantable donor cells. Here, we review the reprogramming process of somatic cells into induced PSCs and associated mechanisms with emphasis on self-renewal, epigenetic control, mitochondrial bioenergetics, sub-states of pluripotency, naive ground state, naive and primed. A meta-analysis identified genes expressed exclusively in the inner cell mass and in the naive but not in the primed pluripotent state. We propose these as additional biomarkers defining naive PSCs.This article is part of the theme issue 'Designer human tissue: coming to a lab near you'.

New tools for oligonucleotide fingerprinting.

Oligonucleotide fingerprinting is an attractive, high-throughput complement to tag sequencing methods to determine the spectrum and abundance of genes in cDNA libraries. This method currently relies on the sequential hybridizations of short, radioactively labeled DNA oligonucleotides to clone arrays. Here, we describe a new environment that substantially improves this technology. Fluorescently labeled peptide nucleic acid (PNA) oligonucleotides are used as hybridization probes. Hybridization results are recorded with a large-field, high-resolution laser scanner developed for this purpose. Automated image analysis allows easy handling of large numbers of hybridization images. Signal interference effects, which limit the gridding density in the radioactive approach, are strongly reduced. The sensitivity of the fluorescence detection demonstrated permits the convenient use of nylon membranes. Hybridization data quality is improved, and its generation is substantially accelerated, simplified, and less expensive.

Automated image analysis for array hybridization experiments.

MOTIVATION: Image analysis is a major part of data evaluation for array hybridization experiments in molecular biology. The program presented here is designed to analyze automatically images from hybridization experiments with various arrangements: different kinds of probes (oligonucleotides or complex probes), different supports (nylon filters or glass slides), different labeling of probes (radioactively or fluorescently). The program is currently applied to oligonucleotide fingerprinting projects and complex hybridizations. The only precondition for the use of the program is that the targets are arrayed in a grid, which can be approximately transformed to an orthogonal equidistant grid by a projective mapping. RESULTS: We demonstrate that our program can cope with the following problems: global distortion of the grid, missing of grid nodes, local deviation of the spot from its specified grid position. This is checked by different quality measures. The image analysis of oligonucleotide fingerprint experiments on an entire genetic library is used, in clustering procedures, to group related clones together. The results show that the program yields automatically generated high quality input data for follow up analysis such as clustering procedures. AVAILABILITY: The executable files will be available upon request for academics.