Molecular data show conserved DNA locations distinguishing lung cancer subtypes and regulation of immune genes.

INTRODUCTION: Non-small-cell lung cancer exhibits a range of transcriptional and epigenetic patterns that not only define distinct phenotypes, but may also govern immune related genes, which have a major impact on survival. METHODS: We used open-source RNA expression and DNA methylation data of the Cancer Genome Atlas with matched non-cancerous tissue to evaluate whether these pretreatment molecular patterns also influenced genes related to the immune system and overall survival. RESULTS: The distinction between lung adenocarcinoma and squamous cell carcinoma are determined by 1083 conserved methylation loci and RNA expression of 203 genes which differ for >80 % of patients between the two subtypes. Using the RNA expression profiles of 6 genes, more than 95 % of patients could be correctly classified as having either adeno or squamous cell lung cancer. Comparing tumor tissue with matched normal tissue, no differences in RNA expression were found for costimulatory and co-inhibitory genes, nor genes involved in cytokine release. However, genes involved in antigen presentation had a lower expression and a wider distribution in tumor tissue. DISCUSSION: Only a small number of genes, influenced by DNA methylation, determine the lung cancer subtype. The antigen presentation of cancer cells is dysfunctional, while other T cell immune functions appear to remain intact.

Interview with Tom Peters. Father of post-modern corporation speaks out. Interview by Richard D. Brennan, Jr.

Tom Peters has been selected as the opening Keynote speaker at the National Association for Home Care and Hospice's Annual Meeting in Seattle, Washington on October 23-26, 2005. Peters has been described by the Los Angeles Times as the "father of the post-modern corporation." The New Yorker said, "In no small part, what American corporations have become is what Peters has encouraged them to be." Fortune called Tom Peters the top guru of management, and compares him to Ralph Waldo Emerson, Henry David Thoreau, Walt Whitman, and H.L. Mencken. The Economist tagged him the Uber-guru; and BusinessWeek's take on his "unconventional views" led them to label him "business's best friend and worst nightmare."

Performance reassessment of a real-time seizure-detection algorithm on long ECoG series.

PURPOSE: Automated seizure detection and blockage requires highly sensitive and specific algorithms. This study reassessed the performance of an algorithm by using a more extensive database than that of a previous study and its suitability for safety/efficacy closed-loop studies to block seizures in humans. METHODS: Up to eight electrocorticography (EcoG) channels from 15 subjects were analyzed off-line. Visual and computerized analyses of the data were performed by different (blinded) investigators. Independent visual analysis also was performed for clinical seizures and for detections identified only by the algorithm. The following were computed: FP rate, number of FNs, latency to automated detection, warning rate for clinical onset and warning times, seizure duration/intensity, and interrater agreement. Adaptations to improve performance were performed when indicated. RESULTS: Fourteen subjects met inclusion criteria. Generic algorithm "relative sensitivity" for clinical seizures was 100%; two undetected subclinical seizures and two unclassified seizures were captured after adaptation. FPs/day were zero in seven and fewer than one in an additional three subjects. Adaptations for four subjects with greater than 1 FP/day (7.7-66.6/day) reduced the rate to 0 in one subject and to fewer than five FP/day (1.7-4.2/day) in the remainder. Generic latency to automated detection was <5 s in eight of 13 subjects, and in 12 of 13 after adaptation. Detections provided warning of clinical onset in three of four subjects in whom it always followed electrographic onset, and in four of four after adaptation. Interrater agreement was low for FPs and EDs. CONCLUSIONS: The generic algorithm demonstrated high sensitivity, specificity, and speed, characteristics further enhanced by adaptation. This algorithm is well suited for seizure detection/warning and use in safety/efficacy closed-loop therapy studies.