Gene expression profiling for molecular distinction and characterization of laser captured primary lung cancers

<p>Abstract</p> <p>Methods</p> <p>We examined gene expression profiles of tumor cells from 29 untreated patients with lung cancer (10 adenocarcinomas (AC), 10 squamous cell carcinomas (SCC), and 9 small cell lung cancer (SCLC)) in comparison to 5 samples of normal lung tissue (NT). The European and American methodological quality guidelines for microarray experiments were followed, including the stipulated use of laser capture microdissection for separation and purification of the lung cancer tumor cells from surrounding tissue.</p> <p>Results</p> <p>Based on differentially expressed genes, different lung cancer samples could be distinguished from each other and from normal lung tissue using hierarchical clustering. Comparing AC, SCC and SCLC with NT, we found 205, 335 and 404 genes, respectively, that were at least 2-fold differentially expressed (estimated false discovery rate: < 2.6%). Different lung cancer subtypes had distinct molecular phenotypes, which also reflected their biological characteristics. Differentially expressed genes in human lung tumors which may be of relevance in the respective lung cancer subtypes were corroborated by quantitative real-time PCR.</p> <p>Genetic programming (GP) was performed to construct a classifier for distinguishing between AC, SCC, SCLC, and NT. Forty genes, that could be used to correctly classify the tumor or NT samples, have been identified. In addition, all samples from an independent test set of 13 further tumors (AC or SCC) were also correctly classified.</p> <p>Conclusion</p> <p>The data from this research identified potential candidate genes which could be used as the basis for the development of diagnostic tools and lung tumor type-specific targeted therapies.</p

A Process Model for Generating and Evaluating Ideas : The Use of Machine Learning and Visual Analytics to Support Idea Mining

The significance and possibilities of idea generation and evaluation are increasing due to the increasing demands for digital innovation and the abundance of textual data. Textual data such as social media, publications, patents, documents, etc. are used to generate ideas, yet manual analysis is affected by bias and subjectivity. Machine learning and visual analytics tools could be used to support idea generation and evaluation, referred to as idea mining, to unlock the potential of voluminous textual data. Idea mining is applied to support the extraction of useful information from textual data. However, existing literature merely focuses on the outcome and overlooks structuring and standardizing the process itself. In this paper, to support idea mining, we designed a model following design science research, which overlaps with the Cross-Industry-Standard-Process for Data Mining (CRISP-DM) process and adapts well-established models for technology scouting. The first layer presents and business layer, where tasks performed by technology scouts, incubators, accelerators, consultants, and contest managers are detailed. The second layer presents the technical layer where tasks performed by data scientists, data engineers, and similar experts are detailed overlapping with CRISP-DM. For future research, we suggest an ex-post evaluation and customization of the model to other techniques of idea mining

Purchasing Involvement in Discontinuous Innovation: An Emerging Research Agenda

International audienceBuilding on a systematic review of the literature, we define and discuss why and how purchasing needs to be involved in the discontinuous innovation process. We argue that purchasing involvement in NPD should be considered mainly when the customer firm faces discontinuous innovation. Seeking to promote this emerging research agenda, we present three propositions to focus future studies and inspire practices: (a) technology sourcing and scanning out of the boundary of the supply base is an important stake to support discontinuous innovation as (b) to form an ambidextrous purchasing organization and (c) to develop absorptive capacity within purchasing function. The paper concludes by summarizing the conceptual implications of the paper, outlining some initial managerial recommendations